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Title: Dynamical Isometry is Achieved in Residual Networks in a Universal Way for any Activation Function,
Abstract: We demonstrate that in residual neural networks (ResNets) dynamical isometry
is achievable irrespectively of the activation function used. We do that by
deriving, with the help of Free Probability and Random Matrix Theories, a
universal formula for the spectral density of the input-output Jacobian at
initialization, in the large network width and depth limit. The resulting
singular value spectrum depends on a single parameter, which we calculate for a
variety of popular activation functions, by analyzing the signal propagation in
the artificial neural network. We corroborate our results with numerical
simulations of both random matrices and ResNets applied to the CIFAR-10
classification problem. Moreover, we study the consequence of this universal
behavior for the initial and late phases of the learning processes. We conclude
by drawing attention to the simple fact, that initialization acts as a
confounding factor between the choice of activation function and the rate of
learning. We propose that in ResNets this can be resolved based on our results,
by ensuring the same level of dynamical isometry at initialization. | [
0,
0,
0,
1,
0,
0
] | [
"Computer Science",
"Mathematics"
] |
Title: Numerical Observation of Parafermion Zero Modes and their Stability in 2D Topological States,
Abstract: The possibility of realizing non-Abelian excitations (non-Abelions) in
two-dimensional (2D) Abelian states of matter has generated a lot of interest
recently. A well-known example of such non-Abelions are parafermion zeros modes
(PFZMs) which can be realized at the endpoints of the so called genons in
fractional quantum Hall (FQH) states or fractional Chern insulators (FCIs). In
this letter, we discuss some known signatures of PFZMs and also introduce some
novel ones. In particular, we show that the topological entanglement entropy
(TEE) shifts by a quantized value after crossing PFZMs. Utilizing those
signatures, we present the first large scale numerical study of PFZMs and their
stability against perturbations in both FQH states and FCIs within the
density-Matrix-Renormalization-Group (DMRG) framework. Our results can help
build a closer connection with future experiments on FQH states with genons. | [
0,
1,
0,
0,
0,
0
] | [
"Physics",
"Mathematics"
] |
Title: Stochastic Optimal Control of Epidemic Processes in Networks,
Abstract: We approach the development of models and control strategies of
susceptible-infected-susceptible (SIS) epidemic processes from the perspective
of marked temporal point processes and stochastic optimal control of stochastic
differential equations (SDEs) with jumps. In contrast to previous work, this
novel perspective is particularly well-suited to make use of fine-grained data
about disease outbreaks and lets us overcome the shortcomings of current
control strategies. Our control strategy resorts to treatment intensities to
determine who to treat and when to do so to minimize the amount of infected
individuals over time. Preliminary experiments with synthetic data show that
our control strategy consistently outperforms several alternatives. Looking
into the future, we believe our methodology provides a promising step towards
the development of practical data-driven control strategies of epidemic
processes. | [
1,
0,
0,
0,
0,
0
] | [
"Mathematics",
"Statistics",
"Quantitative Biology"
] |
Title: Improved upper bounds in the moving sofa problem,
Abstract: The moving sofa problem, posed by L. Moser in 1966, asks for the planar shape
of maximal area that can move around a right-angled corner in a hallway of unit
width. It is known that a maximal area shape exists, and that its area is at
least 2.2195... - the area of an explicit construction found by Gerver in 1992
- and at most $2\sqrt{2}=2.82...$, with the lower bound being conjectured as
the true value. We prove a new and improved upper bound of 2.37. The method
involves a computer-assisted proof scheme that can be used to rigorously derive
further improved upper bounds that converge to the correct value. | [
0,
0,
1,
0,
0,
0
] | [
"Mathematics",
"Computer Science"
] |
Title: Neural correlates of episodic memory in the Memento cohort,
Abstract: IntroductionThe free and cued selective reminding test is used to identify
memory deficits in mild cognitive impairment and demented patients. It allows
assessing three processes: encoding, storage, and recollection of verbal
episodic memory.MethodsWe investigated the neural correlates of these three
memory processes in a large cohort study. The Memento cohort enrolled 2323
outpatients presenting either with subjective cognitive decline or mild
cognitive impairment who underwent cognitive, structural MRI and, for a subset,
fluorodeoxyglucose--positron emission tomography evaluations.ResultsEncoding
was associated with a network including parietal and temporal cortices; storage
was mainly associated with entorhinal and parahippocampal regions, bilaterally;
retrieval was associated with a widespread network encompassing frontal
regions.DiscussionThe neural correlates of episodic memory processes can be
assessed in large and standardized cohorts of patients at risk for Alzheimer's
disease. Their relation to pathophysiological markers of Alzheimer's disease
remains to be studied. | [
0,
0,
0,
0,
1,
0
] | [
"Quantitative Biology"
] |
Title: Extended quantum field theory, index theory and the parity anomaly,
Abstract: We use techniques from functorial quantum field theory to provide a geometric
description of the parity anomaly in fermionic systems coupled to background
gauge and gravitational fields on odd-dimensional spacetimes. We give an
explicit construction of a geometric cobordism bicategory which incorporates
general background fields in a stack, and together with the theory of symmetric
monoidal bicategories we use it to provide the concrete forms of invertible
extended quantum field theories which capture anomalies in both the path
integral and Hamiltonian frameworks. Specialising this situation by using the
extension of the Atiyah-Patodi-Singer index theorem to manifolds with corners
due to Loya and Melrose, we obtain a new Hamiltonian perspective on the parity
anomaly. We compute explicitly the 2-cocycle of the projective representation
of the gauge symmetry on the quantum state space, which is defined in a
parity-symmetric way by suitably augmenting the standard chiral fermionic Fock
spaces with Lagrangian subspaces of zero modes of the Dirac Hamiltonian that
naturally appear in the index theorem. We describe the significance of our
constructions for the bulk-boundary correspondence in a large class of
time-reversal invariant gauge-gravity symmetry-protected topological phases of
quantum matter with gapless charged boundary fermions, including the standard
topological insulator in 3+1 dimensions. | [
0,
1,
1,
0,
0,
0
] | [
"Physics",
"Mathematics"
] |
Title: Learning Graphical Models Using Multiplicative Weights,
Abstract: We give a simple, multiplicative-weight update algorithm for learning
undirected graphical models or Markov random fields (MRFs). The approach is
new, and for the well-studied case of Ising models or Boltzmann machines, we
obtain an algorithm that uses a nearly optimal number of samples and has
quadratic running time (up to logarithmic factors), subsuming and improving on
all prior work. Additionally, we give the first efficient algorithm for
learning Ising models over general alphabets.
Our main application is an algorithm for learning the structure of t-wise
MRFs with nearly-optimal sample complexity (up to polynomial losses in
necessary terms that depend on the weights) and running time that is
$n^{O(t)}$. In addition, given $n^{O(t)}$ samples, we can also learn the
parameters of the model and generate a hypothesis that is close in statistical
distance to the true MRF. All prior work runs in time $n^{\Omega(d)}$ for
graphs of bounded degree d and does not generate a hypothesis close in
statistical distance even for t=3. We observe that our runtime has the correct
dependence on n and t assuming the hardness of learning sparse parities with
noise.
Our algorithm--the Sparsitron-- is easy to implement (has only one parameter)
and holds in the on-line setting. Its analysis applies a regret bound from
Freund and Schapire's classic Hedge algorithm. It also gives the first solution
to the problem of learning sparse Generalized Linear Models (GLMs). | [
1,
0,
1,
1,
0,
0
] | [
"Computer Science",
"Statistics",
"Mathematics"
] |
Title: Neutron response of PARIS phoswich detector,
Abstract: We have studied neutron response of PARIS phoswich [LaBr$_3$(Ce)-NaI(Tl)]
detector which is being developed for measuring the high energy (E$_{\gamma}$ =
5 - 30 MeV) $\gamma$ rays emitted from the decay of highly collective states in
atomic nuclei. The relative neutron detection efficiency of LaBr$_3$(Ce) and
NaI(Tl) crystal of the phoswich detector has been measured using the
time-of-flight (TOF) and pulse shape discrimination (PSD) technique in the
energy range of E$_n$ = 1 - 9 MeV and compared with the GEANT4 based
simulations. It has been found that for E$_n$ $>$ 3 MeV, $\sim$ 95 \% of
neutrons have the primary interaction in the LaBr$_3$(Ce) crystal, indicating
that a clear n-$\gamma$ separation can be achieved even at $\sim$15 cm flight
path. | [
0,
1,
0,
0,
0,
0
] | [
"Physics"
] |
Title: Swarm robotics in wireless distributed protocol design for coordinating robots involved in cooperative tasks,
Abstract: The mine detection in an unexplored area is an optimization problem where
multiple mines, randomly distributed throughout an area, need to be discovered
and disarmed in a minimum amount of time. We propose a strategy to explore an
unknown area, using a stigmergy approach based on ants behavior, and a novel
swarm based protocol to recruit and coordinate robots for disarming the mines
cooperatively. Simulation tests are presented to show the effectiveness of our
proposed Ant-based Task Robot Coordination (ATRC) with only the exploration
task and with both exploration and recruiting strategies. Multiple minimization
objectives have been considered: the robots' recruiting time and the overall
area exploration time. We discuss, through simulation, different cases under
different network and field conditions, performed by the robots. The results
have shown that the proposed decentralized approaches enable the swarm of
robots to perform cooperative tasks intelligently without any central control. | [
1,
0,
0,
0,
0,
0
] | [
"Computer Science",
"Robotics"
] |
Title: Corruption-free scheme of entering into contract: mathematical model,
Abstract: The main purpose of this paper is to formalize the modelling process,
analysis and mathematical definition of corruption when entering into a
contract between principal agent and producers. The formulation of the problem
and the definition of concepts for the general case are considered. For
definiteness, all calculations and formulas are given for the case of three
producers, one principal agent and one intermediary. Economic analysis of
corruption allowed building a mathematical model of interaction between agents.
Financial resources distribution problem in a contract with a corrupted
intermediary is considered.Then proposed conditions for corruption emergence
and its possible consequences. Optimal non-corruption schemes of financial
resources distribution in a contract are formed, when principal agent's choice
is limited first only by asymmetrical information and then also by external
influences.Numerical examples suggesting optimal corruption-free agents'
behaviour are presented. | [
0,
0,
0,
0,
0,
1
] | [
"Mathematics",
"Quantitative Finance"
] |
Title: A Multiobjective Approach to Multimicrogrid System Design,
Abstract: The main goal of this paper is to design a market operator (MO) and a
distribution network operator (DNO) for a network of microgrids in
consideration of multiple objectives. This is a high-level design and only
those microgrids with nondispatchable renewable energy sources are considered.
For a power grid in the network, the net value derived from providing power to
the network must be maximized. For a microgrid, it is desirable to maximize the
net gain derived from consuming the received power. Finally, for an independent
system operator, stored energy levels at microgrids must be maintained as close
as possible to storage capacity to secure network emergency operation. To
achieve these objectives, a multiobjective approach is proposed. The price
signal generated by the MO and power distributed by the DNO are assigned based
on a Pareto optimal solution of a multiobjective optimization problem. By using
the proposed approach, a fair scheme that does not advantage one particular
objective can be attained. Simulations are provided to validate the proposed
methodology. | [
1,
0,
0,
0,
0,
0
] | [
"Computer Science",
"Mathematics",
"Quantitative Finance"
] |
Title: Calculating the closed ordinal Ramsey number $R^{cl}(ω\cdot 2,3)^2$,
Abstract: We show that $R^{cl}(\omega\cdot 2,3)^2$ is equal to $\omega^3\cdot 2$. | [
0,
0,
1,
0,
0,
0
] | [
"Mathematics"
] |
Title: Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discovery,
Abstract: Obtaining models that capture imaging markers relevant for disease
progression and treatment monitoring is challenging. Models are typically based
on large amounts of data with annotated examples of known markers aiming at
automating detection. High annotation effort and the limitation to a vocabulary
of known markers limit the power of such approaches. Here, we perform
unsupervised learning to identify anomalies in imaging data as candidates for
markers. We propose AnoGAN, a deep convolutional generative adversarial network
to learn a manifold of normal anatomical variability, accompanying a novel
anomaly scoring scheme based on the mapping from image space to a latent space.
Applied to new data, the model labels anomalies, and scores image patches
indicating their fit into the learned distribution. Results on optical
coherence tomography images of the retina demonstrate that the approach
correctly identifies anomalous images, such as images containing retinal fluid
or hyperreflective foci. | [
1,
0,
0,
0,
0,
0
] | [
"Computer Science",
"Quantitative Biology"
] |
Title: ZOOpt: Toolbox for Derivative-Free Optimization,
Abstract: Recent advances of derivative-free optimization allow efficient approximating
the global optimal solutions of sophisticated functions, such as functions with
many local optima, non-differentiable and non-continuous functions. This
article describes the ZOOpt (this https URL) toolbox that
provides efficient derivative-free solvers and are designed easy to use. ZOOpt
provides a Python package for single-thread optimization, and a light-weighted
distributed version with the help of the Julia language for Python described
functions. ZOOpt toolbox particularly focuses on optimization problems in
machine learning, addressing high-dimensional, noisy, and large-scale problems.
The toolbox is being maintained toward ready-to-use tool in real-world machine
learning tasks. | [
0,
0,
0,
1,
0,
0
] | [
"Computer Science",
"Mathematics"
] |
Title: Capacitated Bounded Cardinality Hub Routing Problem: Model and Solution Algorithm,
Abstract: In this paper, we address the Bounded Cardinality Hub Location Routing with
Route Capacity wherein each hub acts as a transshipment node for one directed
route. The number of hubs lies between a minimum and a maximum and the
hub-level network is a complete subgraph. The transshipment operations take
place at the hub nodes and flow transfer time from a hub-level transporter to a
spoke-level vehicle influences spoke- to-hub allocations. We propose a
mathematical model and a branch-and-cut algorithm based on Benders
decomposition to solve the problem. To accelerate convergence, our solution
framework embeds an efficient heuristic producing high-quality solutions in
short computation times. In addition, we show how symmetry can be exploited to
accelerate and improve the performance of our method. | [
0,
0,
1,
0,
0,
0
] | [
"Computer Science",
"Mathematics"
] |
Title: Large Kernel Matters -- Improve Semantic Segmentation by Global Convolutional Network,
Abstract: One of recent trends [30, 31, 14] in network architec- ture design is
stacking small filters (e.g., 1x1 or 3x3) in the entire network because the
stacked small filters is more ef- ficient than a large kernel, given the same
computational complexity. However, in the field of semantic segmenta- tion,
where we need to perform dense per-pixel prediction, we find that the large
kernel (and effective receptive field) plays an important role when we have to
perform the clas- sification and localization tasks simultaneously. Following
our design principle, we propose a Global Convolutional Network to address both
the classification and localization issues for the semantic segmentation. We
also suggest a residual-based boundary refinement to further refine the ob-
ject boundaries. Our approach achieves state-of-art perfor- mance on two public
benchmarks and significantly outper- forms previous results, 82.2% (vs 80.2%)
on PASCAL VOC 2012 dataset and 76.9% (vs 71.8%) on Cityscapes dataset. | [
1,
0,
0,
0,
0,
0
] | [
"Computer Science"
] |
Title: Testing Network Structure Using Relations Between Small Subgraph Probabilities,
Abstract: We study the problem of testing for structure in networks using relations
between the observed frequencies of small subgraphs. We consider the statistics
\begin{align*} T_3 & =(\text{edge frequency})^3 - \text{triangle frequency}\\
T_2 & =3(\text{edge frequency})^2(1-\text{edge frequency}) - \text{V-shape
frequency} \end{align*} and prove a central limit theorem for $(T_2, T_3)$
under an Erdős-Rényi null model. We then analyze the power of the
associated $\chi^2$ test statistic under a general class of alternative models.
In particular, when the alternative is a $k$-community stochastic block model,
with $k$ unknown, the power of the test approaches one. Moreover, the
signal-to-noise ratio required is strictly weaker than that required for
community detection. We also study the relation with other statistics over
three-node subgraphs, and analyze the error under two natural algorithms for
sampling small subgraphs. Together, our results show how global structural
characteristics of networks can be inferred from local subgraph frequencies,
without requiring the global community structure to be explicitly estimated. | [
1,
0,
1,
1,
0,
0
] | [
"Statistics",
"Mathematics",
"Computer Science"
] |
Title: A 3D MHD simulation of SN 1006: a polarized emission study for the turbulent case,
Abstract: Three dimensional magnetohydrodynamical simulations were carried out in order
to perform a new polarization study of the radio emission of the supernova
remnant SN 1006. These simulations consider that the remnant expands into a
turbulent interstellar medium (including both magnetic field and density
perturbations). Based on the referenced-polar angle technique, a statistical
study was done on observational and numerical magnetic field position-angle
distributions. Our results show that a turbulent medium with an adiabatic index
of 1.3 can reproduce the polarization properties of the SN 1006 remnant. This
statistical study reveals itself as a useful tool for obtaining the orientation
of the ambient magnetic field, previous to be swept up by the main supernova
remnant shock. | [
0,
1,
0,
0,
0,
0
] | [
"Physics"
] |
Title: On short cycle enumeration in biregular bipartite graphs,
Abstract: A number of recent works have used a variety of combinatorial constructions
to derive Tanner graphs for LDPC codes and some of these have been shown to
perform well in terms of their probability of error curves and error floors.
Such graphs are bipartite and many of these constructions yield biregular
graphs where the degree of left vertices is a constant $c+1$ and that of the
right vertices is a constant $d+1$. Such graphs are termed $(c+1,d+1)$
biregular bipartite graphs here. One property of interest in such work is the
girth of the graph and the number of short cycles in the graph, cycles of
length either the girth or slightly larger. Such numbers have been shown to be
related to the error floor of the probability of error curve of the related
LDPC code. Using known results of graph theory, it is shown how the girth and
the number of cycles of length equal to the girth may be computed for these
$(c+1,d+1)$ biregular bipartite graphs knowing only the parameters $c$ and $d$
and the numbers of left and right vertices. While numerous algorithms to
determine the number of short cycles in arbitrary graphs exist, the reduction
of the problem from an algorithm to a computation for these biregular bipartite
graphs is of interest. | [
1,
0,
1,
0,
0,
0
] | [
"Computer Science",
"Mathematics"
] |
Title: Exhaled breath barbotage: a new method for pulmonary surfactant dysfunction assessment,
Abstract: Exhaled air contains aerosol of submicron droplets of the alveolar lining
fluid (ALF), which are generated in the small airways of a human lung. Since
the exhaled particles are micro-samples of the ALF, their trapping opens up an
opportunity to collect non-invasively a native material from respiratory tract.
Recent studies of the particle characteristics (such as size distribution,
concentration and composition) in healthy and diseased subjects performed under
various conditions have demonstrated a high potential of the analysis of
exhaled aerosol droplets for identifying and monitoring pathological processes
in the ALF. In this paper we present a new method for sampling of aerosol
particles during the exhaled breath barbotage (EBB) through liquid. The
barbotage procedure results in accumulation of the pulmonary surfactant, being
the main component of ALF, on the liquid surface, which makes possible the
study its surface properties. We also propose a data processing algorithm to
evaluate the surface pressure ($\pi$) -- surface concentration ($\Gamma$)
isotherm from the raw data measured in a Langmuir trough. Finally, we analyze
the $(\pi-\Gamma)$ isotherms obtained for the samples collected in the groups
of healthy volunteers and patients with pulmonary tuberculosis and compare them
with the isotherm measured for the artificial pulmonary surfactant. | [
0,
1,
0,
0,
0,
0
] | [
"Quantitative Biology"
] |
Title: A Computational Study of the Role of Tonal Tension in Expressive Piano Performance,
Abstract: Expressive variations of tempo and dynamics are an important aspect of music
performances, involving a variety of underlying factors. Previous work has
showed a relation between such expressive variations (in particular expressive
tempo) and perceptual characteristics derived from the musical score, such as
musical expectations, and perceived tension. In this work we use a
computational approach to study the role of three measures of tonal tension
proposed by Herremans and Chew (2016) in the prediction of expressive
performances of classical piano music. These features capture tonal
relationships of the music represented in Chew's spiral array model, a three
dimensional representation of pitch classes, chords and keys constructed in
such a way that spatial proximity represents close tonal relationships. We use
non-linear sequential models (recurrent neural networks) to assess the
contribution of these features to the prediction of expressive dynamics and
expressive tempo using a dataset of Mozart piano sonatas performed by a
professional concert pianist. Experiments of models trained with and without
tonal tension features show that tonal tension helps predict change of tempo
and dynamics more than absolute tempo and dynamics values. Furthermore, the
improvement is stronger for dynamics than for tempo. | [
1,
0,
0,
0,
0,
0
] | [
"Computer Science",
"Quantitative Biology"
] |
Title: Self-organization and the Maximum Empower Principle in the Framework of max-plus Algebra,
Abstract: Self-organization is a process where order of a whole system arises out of
local interactions between small components of a system.
Emergy, defined as the amount of (solar) energy used to make a product or a
service, is becoming an important ecological indicator. To explain observed
self-organization of systems by emergy the Maximum Empower Principle (MEP) was
proposed initially without a mathematical formulation.
Emergy analysis is based on four rules called emergy algebra. Most of emergy
computations in steady state are in fact approximate results, which rely on
linear algebra. In such a context, a mathematical formulation of the MEP has
been proposed by Giannantoni (2002).
In 2012 Le Corre and the second author of this paper have proposed a rigorous
mathematical framework for emergy analysis. They established that the exact
computation of emergy is based on the so-called max-plus algebra and seven
coherent axioms that replace the emergy algebra. In this paper the MEP in
steady state is formalized in the context of the max-plus algebra and graph
theory. The main concepts of the paper are (a) a particular graph called
'emergy graph', (b) the notion of compatible paths of the emergy graph, and (c)
sets of compatible paths, which are called 'emergy states'. The main results of
the paper are as follows:
(1) Emergy is mathematically expressed as a maximum over all possible emergy
states. (2) The maximum is always reached by an emergy state. (3) Only prevail
emergy states for which the maximum is reached. | [
1,
1,
0,
0,
0,
0
] | [
"Mathematics",
"Physics"
] |
Title: Planet-driven spiral arms in protoplanetary disks: II. Implications,
Abstract: We examine whether various characteristics of planet-driven spiral arms can
be used to constrain the masses of unseen planets and their positions within
their disks. By carrying out two-dimensional hydrodynamic simulations varying
planet mass and disk gas temperature, we find that a larger number of spiral
arms form with a smaller planet mass and a lower disk temperature. A planet
excites two or more spiral arms interior to its orbit for a range of disk
temperature characterized by the disk aspect ratio $0.04\leq(h/r)_p\leq0.15$,
whereas exterior to a planet's orbit multiple spiral arms can form only in cold
disks with $(h/r)_p \lesssim 0.06$. Constraining the planet mass with the pitch
angle of spiral arms requires accurate disk temperature measurements that might
be challenging even with ALMA. However, the property that the pitch angle of
planet-driven spiral arms decreases away from the planet can be a powerful
diagnostic to determine whether the planet is located interior or exterior to
the observed spirals. The arm-to-arm separations increase as a function of
planet mass, consistent with previous studies; however, the exact slope depends
on disk temperature as well as the radial location where the arm-to-arm
separations are measured. We apply these diagnostics to the spiral arms seen in
MWC 758 and Elias 2-27. As shown in Bae et al. (2017), planet-driven spiral
arms can create concentric rings and gaps, which can produce more dominant
observable signature than spiral arms under certain circumstances. We discuss
the observability of planet-driven spiral arms versus rings and gaps. | [
0,
1,
0,
0,
0,
0
] | [
"Physics"
] |
Title: Ideal structure and pure infiniteness of ample groupoid $C^*$-algebras,
Abstract: In this paper, we study the ideal structure of reduced $C^*$-algebras
$C^*_r(G)$ associated to étale groupoids $G$. In particular, we characterize
when there is a one-to-one correspondence between the closed, two-sided ideals
in $C_r^*(G)$ and the open invariant subsets of the unit space $G^{(0)}$ of
$G$. As a consequence, we show that if $G$ is an inner exact, essentially
principal, ample groupoid, then $C_r^*(G)$ is (strongly) purely infinite if and
only if every non-zero projection in $C_0(G^{(0)})$ is properly infinite in
$C_r^*(G)$. We also establish a sufficient condition on the ample groupoid $G$
that ensures pure infiniteness of $C_r^*(G)$ in terms of paradoxicality of
compact open subsets of the unit space $G^{(0)}$.
Finally, we introduce the type semigroup for ample groupoids and also obtain
a dichotomy result: Let $G$ be an ample groupoid with compact unit space which
is minimal and topologically principal. If the type semigroup is almost
unperforated, then $C_r^*(G)$ is a simple $C^*$-algebra which is either stably
finite or strongly purely infinite. | [
0,
0,
1,
0,
0,
0
] | [
"Mathematics",
"Physics"
] |
Title: Multilevel Sequential Monte Carlo with Dimension-Independent Likelihood-Informed Proposals,
Abstract: In this article we develop a new sequential Monte Carlo (SMC) method for
multilevel (ML) Monte Carlo estimation. In particular, the method can be used
to estimate expectations with respect to a target probability distribution over
an infinite-dimensional and non-compact space as given, for example, by a
Bayesian inverse problem with Gaussian random field prior. Under suitable
assumptions the MLSMC method has the optimal $O(\epsilon^{-2})$ bound on the
cost to obtain a mean-square error of $O(\epsilon^2)$. The algorithm is
accelerated by dimension-independent likelihood-informed (DILI) proposals
designed for Gaussian priors, leveraging a novel variation which uses empirical
sample covariance information in lieu of Hessian information, hence eliminating
the requirement for gradient evaluations. The efficiency of the algorithm is
illustrated on two examples: inversion of noisy pressure measurements in a PDE
model of Darcy flow to recover the posterior distribution of the permeability
field, and inversion of noisy measurements of the solution of an SDE to recover
the posterior path measure. | [
0,
0,
0,
1,
0,
0
] | [
"Statistics",
"Mathematics",
"Computer Science"
] |
Title: On (in)stabilities of perturbations in mimetic models with higher derivatives,
Abstract: Usually when applying the mimetic model to the early universe, higher
derivative terms are needed to promote the mimetic field to be dynamical.
However such models suffer from the ghost and/or the gradient instabilities and
simple extensions cannot cure this pathology. We point out in this paper that
it is possible to overcome this difficulty by considering the direct couplings
of the higher derivatives of the mimetic field to the curvature of the
spacetime. | [
0,
1,
0,
0,
0,
0
] | [
"Physics"
] |
Title: METAGUI 3: a graphical user interface for choosing the collective variables in molecular dynamics simulations,
Abstract: Molecular dynamics (MD) simulations allow the exploration of the phase space
of biopolymers through the integration of equations of motion of their
constituent atoms. The analysis of MD trajectories often relies on the choice
of collective variables (CVs) along which the dynamics of the system is
projected. We developed a graphical user interface (GUI) for facilitating the
interactive choice of the appropriate CVs. The GUI allows: defining
interactively new CVs; partitioning the configurations into microstates
characterized by similar values of the CVs; calculating the free energies of
the microstates for both unbiased and biased (metadynamics) simulations;
clustering the microstates in kinetic basins; visualizing the free energy
landscape as a function of a subset of the CVs used for the analysis. A simple
mouse click allows one to quickly inspect structures corresponding to specific
points in the landscape. | [
0,
1,
0,
0,
0,
0
] | [
"Quantitative Biology",
"Physics",
"Computer Science"
] |
Title: Model compression as constrained optimization, with application to neural nets. Part II: quantization,
Abstract: We consider the problem of deep neural net compression by quantization: given
a large, reference net, we want to quantize its real-valued weights using a
codebook with $K$ entries so that the training loss of the quantized net is
minimal. The codebook can be optimally learned jointly with the net, or fixed,
as for binarization or ternarization approaches. Previous work has quantized
the weights of the reference net, or incorporated rounding operations in the
backpropagation algorithm, but this has no guarantee of converging to a
loss-optimal, quantized net. We describe a new approach based on the recently
proposed framework of model compression as constrained optimization
\citep{Carreir17a}. This results in a simple iterative "learning-compression"
algorithm, which alternates a step that learns a net of continuous weights with
a step that quantizes (or binarizes/ternarizes) the weights, and is guaranteed
to converge to local optimum of the loss for quantized nets. We develop
algorithms for an adaptive codebook or a (partially) fixed codebook. The latter
includes binarization, ternarization, powers-of-two and other important
particular cases. We show experimentally that we can achieve much higher
compression rates than previous quantization work (even using just 1 bit per
weight) with negligible loss degradation. | [
1,
0,
1,
1,
0,
0
] | [
"Computer Science",
"Statistics"
] |
Title: Three Skewed Matrix Variate Distributions,
Abstract: Three-way data can be conveniently modelled by using matrix variate
distributions. Although there has been a lot of work for the matrix variate
normal distribution, there is little work in the area of matrix skew
distributions. Three matrix variate distributions that incorporate skewness, as
well as other flexible properties such as concentration, are discussed.
Equivalences to multivariate analogues are presented, and moment generating
functions are derived. Maximum likelihood parameter estimation is discussed,
and simulated data is used for illustration. | [
0,
0,
1,
1,
0,
0
] | [
"Mathematics",
"Statistics"
] |
Title: Direct Estimation of Regional Wall Thicknesses via Residual Recurrent Neural Network,
Abstract: Accurate estimation of regional wall thicknesses (RWT) of left ventricular
(LV) myocardium from cardiac MR sequences is of significant importance for
identification and diagnosis of cardiac disease. Existing RWT estimation still
relies on segmentation of LV myocardium, which requires strong prior
information and user interaction. No work has been devoted into direct
estimation of RWT from cardiac MR images due to the diverse shapes and
structures for various subjects and cardiac diseases, as well as the complex
regional deformation of LV myocardium during the systole and diastole phases of
the cardiac cycle. In this paper, we present a newly proposed Residual
Recurrent Neural Network (ResRNN) that fully leverages the spatial and temporal
dynamics of LV myocardium to achieve accurate frame-wise RWT estimation. Our
ResRNN comprises two paths: 1) a feed forward convolution neural network (CNN)
for effective and robust CNN embedding learning of various cardiac images and
preliminary estimation of RWT from each frame itself independently, and 2) a
recurrent neural network (RNN) for further improving the estimation by modeling
spatial and temporal dynamics of LV myocardium. For the RNN path, we design for
cardiac sequences a Circle-RNN to eliminate the effect of null hidden input for
the first time-step. Our ResRNN is capable of obtaining accurate estimation of
cardiac RWT with Mean Absolute Error of 1.44mm (less than 1-pixel error) when
validated on cardiac MR sequences of 145 subjects, evidencing its great
potential in clinical cardiac function assessment. | [
1,
0,
0,
0,
0,
0
] | [
"Computer Science",
"Quantitative Biology"
] |
Title: Non-dipole recollision-gated double ionization and observable effects,
Abstract: Using a three-dimensional semiclassical model, we study double ionization for
strongly-driven He fully accounting for magnetic field effects. For linearly
and slightly elliptically polarized laser fields, we show that recollisions and
the magnetic field combined act as a gate. This gate favors more transverse -
with respect to the electric field - initial momenta of the tunneling electron
that are opposite to the propagation direction of the laser field. In the
absence of non-dipole effects, the transverse initial momentum is symmetric
with respect to zero. We find that this asymmetry in the transverse initial
momentum gives rise to an asymmetry in a double ionization observable. Finally,
we show that this asymmetry in the transverse initial momentum of the tunneling
electron accounts for a recently-reported unexpectedly large average sum of the
electron momenta parallel to the propagation direction of the laser field. | [
0,
1,
0,
0,
0,
0
] | [
"Physics"
] |
Title: The exit time finite state projection scheme: bounding exit distributions and occupation measures of continuous-time Markov chains,
Abstract: We introduce the exit time finite state projection (ETFSP) scheme, a
truncation-based method that yields approximations to the exit distribution and
occupation measure associated with the time of exit from a domain (i.e., the
time of first passage to the complement of the domain) of time-homogeneous
continuous-time Markov chains. We prove that: (i) the computed approximations
bound the measures from below; (ii) the total variation distances between the
approximations and the measures decrease monotonically as states are added to
the truncation; and (iii) the scheme converges, in the sense that, as the
truncation tends to the entire state space, the total variation distances tend
to zero. Furthermore, we give a computable bound on the total variation
distance between the exit distribution and its approximation, and we delineate
the cases in which the bound is sharp. We also revisit the related finite state
projection scheme and give a comprehensive account of its theoretical
properties. We demonstrate the use of the ETFSP scheme by applying it to two
biological examples: the computation of the first passage time associated with
the expression of a gene, and the fixation times of competing species subject
to demographic noise. | [
0,
0,
0,
0,
1,
0
] | [
"Mathematics",
"Statistics",
"Quantitative Biology"
] |
Title: Ontological Multidimensional Data Models and Contextual Data Qality,
Abstract: Data quality assessment and data cleaning are context-dependent activities.
Motivated by this observation, we propose the Ontological Multidimensional Data
Model (OMD model), which can be used to model and represent contexts as
logic-based ontologies. The data under assessment is mapped into the context,
for additional analysis, processing, and quality data extraction. The resulting
contexts allow for the representation of dimensions, and multidimensional data
quality assessment becomes possible. At the core of a multidimensional context
we include a generalized multidimensional data model and a Datalog+/- ontology
with provably good properties in terms of query answering. These main
components are used to represent dimension hierarchies, dimensional
constraints, dimensional rules, and define predicates for quality data
specification. Query answering relies upon and triggers navigation through
dimension hierarchies, and becomes the basic tool for the extraction of quality
data. The OMD model is interesting per se, beyond applications to data quality.
It allows for a logic-based, and computationally tractable representation of
multidimensional data, extending previous multidimensional data models with
additional expressive power and functionalities. | [
1,
0,
0,
0,
0,
0
] | [
"Computer Science",
"Mathematics"
] |
Title: Improved Bounds for Online Dominating Sets of Trees,
Abstract: The online dominating set problem is an online variant of the minimum
dominating set problem, which is one of the most important NP-hard problems on
graphs. This problem is defined as follows: Given an undirected graph $G = (V,
E)$, in which $V$ is a set of vertices and $E$ is a set of edges. We say that a
set $D \subseteq V$ of vertices is a {\em dominating set} of $G$ if for each $v
\in V \setminus D$, there exists a vertex $u \in D$ such that $\{ u, v \} \in
E$. The vertices are revealed to an online algorithm one by one over time. When
a vertex is revealed, edges between the vertex and vertices revealed in the
past are also revealed. A revelaed subtree is connected at any time.
Immediately after the revelation of each vertex, an online algorithm can choose
vertices which were already revealed irrevocably and must maintain a dominating
set of a graph revealed so far. The cost of an algorithm on a given tree is the
number of vertices chosen by it, and its objective is to minimize the cost.
Eidenbenz (Technical report, Institute of Theoretical Computer Science, ETH
Zürich, 2002) and Boyar et al.\ (SWAT 2016) studied the case in which given
graphs are trees. They designed a deterministic online algorithm whose
competitive ratio is at most three, and proved that a lower bound on the
competitive ratio of any deterministic algorithm is two. In this paper, we also
focus on trees. We establish a matching lower bound for any deterministic
algorithm. Moreover, we design a randomized online algorithm whose competitive
ratio is at most $5/2 = 2.5$, and show that the competitive ratio of any
randomized algorithm is at least $4/3 \approx 1.333$. | [
1,
0,
0,
0,
0,
0
] | [
"Computer Science",
"Mathematics"
] |
Title: Systematical design and three-dimensional simulation of X-ray FEL oscillator for Shanghai Coherent Light Facility,
Abstract: Shanghai Coherent Light Facility (SCLF) is a quasi-CW hard X-ray free
electron laser user facility which is recently proposed. Due to the high
repetition rate, high quality electron beams, it is straightforward to consider
an X-ray free electron laser oscillator (XFELO) operation for SCLF. The main
processes for XFELO design, and parameters optimization of the undulator, X-ray
cavity and electron beam are described. The first three-dimensional X-ray
crystal Bragg diffraction code, named BRIGHT is built, which collaborates
closely with GENESIS and OPC for numerical simulations of XFELO. The XFELO
performances of SCLF is investigated and optimized by theoretical analysis and
numerical simulation. | [
0,
1,
0,
0,
0,
0
] | [
"Physics"
] |
Title: Calibration of a two-state pitch-wise HMM method for note segmentation in Automatic Music Transcription systems,
Abstract: Many methods for automatic music transcription involves a multi-pitch
estimation method that estimates an activity score for each pitch. A second
processing step, called note segmentation, has to be performed for each pitch
in order to identify the time intervals when the notes are played. In this
study, a pitch-wise two-state on/off firstorder Hidden Markov Model (HMM) is
developed for note segmentation. A complete parametrization of the HMM sigmoid
function is proposed, based on its original regression formulation, including a
parameter alpha of slope smoothing and beta? of thresholding contrast. A
comparative evaluation of different note segmentation strategies was performed,
differentiated according to whether they use a fixed threshold, called "Hard
Thresholding" (HT), or a HMM-based thresholding method, called "Soft
Thresholding" (ST). This evaluation was done following MIREX standards and
using the MAPS dataset. Also, different transcription scenarios and recording
natures were tested using three units of the Degradation toolbox. Results show
that note segmentation through a HMM soft thresholding with a data-based
optimization of the {alpha,beta} parameter couple significantly enhances
transcription performance. | [
1,
0,
0,
1,
0,
0
] | [
"Computer Science",
"Statistics"
] |
Title: Reverse approximation of gradient flows as Minimizing Movements: a conjecture by De Giorgi,
Abstract: We consider the Cauchy problem for the gradient flow \begin{equation}
\label{eq:81}
\tag{$\star$}
u'(t)=-\nabla\phi(u(t)),\quad t\ge 0;\quad
u(0)=u_0, \end{equation} generated by a continuously differentiable function
$\phi:\mathbb H \to \mathbb R$ in a Hilbert space $\mathbb H$ and study the
reverse approximation of solutions to ($\star$) by the De Giorgi Minimizing
Movement approach. We prove that if $\mathbb H$ has finite dimension and $\phi$
is quadratically bounded from below (in particular if $\phi$ is Lipschitz) then
for every solution $u$ to ($\star$) (which may have an infinite number of
solutions) there exist perturbations $\phi_\tau:\mathbb H \to \mathbb R \
(\tau>0)$ converging to $\phi$ in the Lipschitz norm such that $u$ can be
approximated by the Minimizing Movement scheme generated by the recursive
minimization of $\Phi(\tau,U,V):=\frac 1{2\tau}|V-U|^2+ \phi_\tau(V)$:
\begin{equation}
\label{eq:abstract}
\tag{$\star\star$}
U_\tau^n\in \operatorname{argmin}_{V\in \mathbb H}
\Phi(\tau,U_\tau^{n-1},V)\quad n\in\mathbb N, \quad U_\tau^0:=u_0.
\end{equation} We show that the piecewise constant interpolations with time
step $\tau > 0$ of all possible selections of solutions
$(U_\tau^n)_{n\in\mathbb N}$ to ($\star\star$) will converge to $u$ as
$\tau\downarrow 0$. This result solves a question raised by Ennio De Giorgi. We
also show that even if $\mathbb H$ has infinite dimension the above
approximation holds for the distinguished class of minimal solutions to
($\star$), that generate all the other solutions to ($\star$) by time
reparametrization. | [
0,
0,
1,
0,
0,
0
] | [
"Mathematics"
] |
Title: Linking de novo assembly results with long DNA reads by dnaasm-link application,
Abstract: Currently, third-generation sequencing techniques, which allow to obtain much
longer DNA reads compared to the next-generation sequencing technologies, are
becoming more and more popular. There are many possibilities to combine data
from next-generation and third-generation sequencing.
Herein, we present a new application called dnaasm-link for linking contigs,
a result of \textit{de novo} assembly of second-generation sequencing data,
with long DNA reads. Our tool includes an integrated module to fill gaps with a
suitable fragment of appropriate long DNA read, which improves the consistency
of the resulting DNA sequences. This feature is very important, in particular
for complex DNA regions, as presented in the paper. Finally, our implementation
outperforms other state-of-the-art tools in terms of speed and memory
requirements, which may enable the usage of the presented application for
organisms with a large genome, which is not possible in~existing applications.
The presented application has many advantages as (i) significant memory
optimization and reduction of computation time (ii) filling the gaps through
the appropriate fragment of a specified long DNA read (iii) reducing number of
spanned and unspanned gaps in the existing genome drafts.
The application is freely available to all users under GNU Library or Lesser
General Public License version 3.0 (LGPLv3). The demo application, docker image
and source code are available at this http URL. | [
0,
0,
0,
0,
1,
0
] | [
"Quantitative Biology",
"Computer Science"
] |
Title: Multiple regimes and coalescence timescales for massive black hole pairs ; the critical role of galaxy formation physics,
Abstract: We discuss the latest results of numerical simulations following the orbital
decay of massive black hole pairs in galaxy mergers. We highlight important
differences between gas-poor and gas-rich hosts, and between orbital evolution
taking place at high redshift as opposed to low redshift. Two effects have a
huge impact and are rather novel in the context of massive black hole binaries.
The first is the increase in characteristic density of galactic nuclei of
merger remnants as galaxies are more compact at high redshift due to the way
dark halo collapse depends on redshift. This leads naturally to hardening
timescales due to 3-body encounters that should decrease by two orders of
magnitude up to $z=4$. It explains naturally the short binary coalescence
timescale, $\sim 10$ Myr, found in novel cosmological simulations that follow
binary evolution from galactic to milliparsec scales. The second one is the
inhomogeneity of the interstellar medium in massive gas-rich disks at high
redshift. In the latter star forming clumps 1-2 orders of magnitude more
massive than local Giant Molecular Clouds (GMCs) can scatter massive black
holes out of the disk plane via gravitational perturbations and direct
encounters. This renders the character of orbital decay inherently stochastic,
often increasing orbital decay timescales by as much as a Gyr. At low redshift
a similar regime is present at scales of $1-10$ pc inside Circumnuclear Gas
Disks (CNDs). In CNDs only massive black holes with masses below $10^7
M_{\odot}$ can be significantly perturbed. They decay to sub-pc separations in
up to $\sim 10^8$ yr rather than the in just a few million years as in a smooth
CND. Finally implications for building robust forecasts of LISA event rates are
discussed | [
0,
1,
0,
0,
0,
0
] | [
"Physics"
] |
Title: Spatio-Temporal Backpropagation for Training High-performance Spiking Neural Networks,
Abstract: Compared with artificial neural networks (ANNs), spiking neural networks
(SNNs) are promising to explore the brain-like behaviors since the spikes could
encode more spatio-temporal information. Although pre-training from ANN or
direct training based on backpropagation (BP) makes the supervised training of
SNNs possible, these methods only exploit the networks' spatial domain
information which leads to the performance bottleneck and requires many
complicated training skills. Another fundamental issue is that the spike
activity is naturally non-differentiable which causes great difficulties in
training SNNs. To this end, we build an iterative LIF model that is more
friendly for gradient descent training. By simultaneously considering the
layer-by-layer spatial domain (SD) and the timing-dependent temporal domain
(TD) in the training phase, as well as an approximated derivative for the spike
activity, we propose a spatio-temporal backpropagation (STBP) training
framework without using any complicated technology. We achieve the best
performance of multi-layered perceptron (MLP) compared with existing
state-of-the-art algorithms over the static MNIST and the dynamic N-MNIST
dataset as well as a custom object detection dataset. This work provides a new
perspective to explore the high-performance SNNs for future brain-like
computing paradigm with rich spatio-temporal dynamics. | [
1,
0,
0,
1,
0,
0
] | [
"Computer Science"
] |
Title: Inverse of a Special Matrix and Application,
Abstract: The matrix inversion is an interesting topic in algebra mathematics. However,
to determine an inverse matrix from a given matrix is required many computation
tools and time resource if the size of matrix is huge. In this paper, we have
shown an inverse closed form for an interesting matrix which has much
applications in communication system. Base on this inverse closed form, the
channel capacity closed form of a communication system can be determined via
the error rate parameter alpha | [
1,
0,
0,
0,
0,
0
] | [
"Mathematics",
"Computer Science"
] |
Title: Gaiotto's Lagrangian subvarieties via loop groups,
Abstract: The purpose of this note is to give a simple proof of the fact that a certain
substack, defined in [2], of the moduli stack $T^{\ast}Bun_G(\Sigma)$ of Higgs
bundles over a curve $\Sigma$, for a connected, simply connected semisimple
group $G$, possesses a Lagrangian structure. The substack, roughly speaking,
consists of images under the moment map of global sections of principal
$G$-bundles over $\Sigma$ twisted by a smooth symplectic variety with a
Hamiltonian $G$-action. | [
0,
0,
1,
0,
0,
0
] | [
"Mathematics",
"Physics"
] |
Title: Kondo Length in Bosonic Lattices,
Abstract: Motivated by the fact that the low-energy properties of the Kondo model can
be effectively simulated in spin chains, we study the realization of the effect
with bond impurities in ultracold bosonic lattices at half-filling. After
presenting a discussion of the effective theory and of the mapping of the
bosonic chain onto a lattice spin Hamiltonian, we provide estimates for the
Kondo length as a function of the parameters of the bosonic model. We point out
that the Kondo length can be extracted from the integrated real space
correlation functions, which are experimentally accessible quantities in
experiments with cold atoms. | [
0,
1,
0,
0,
0,
0
] | [
"Physics"
] |
Title: Macro-molecular data storage with petabyte/cm^3 density, highly parallel read/write operations, and genuine 3D storage capability,
Abstract: Digital information can be encoded in the building-block sequence of
macro-molecules, such as RNA and single-stranded DNA. Methods of "writing" and
"reading" macromolecular strands are currently available, but they are slow and
expensive. In an ideal molecular data storage system, routine operations such
as write, read, erase, store, and transfer must be done reliably and at high
speed within an integrated chip. As a first step toward demonstrating the
feasibility of this concept, we report preliminary results of DNA readout
experiments conducted in miniaturized chambers that are scalable to even
smaller dimensions. We show that translocation of a single-stranded DNA
molecule (consisting of 50 adenosine bases followed by 100 cytosine bases)
through an ion-channel yields a characteristic signal that is attributable to
the 2-segment structure of the molecule. We also examine the dependence of the
rate and speed of molecular translocation on the adjustable parameters of the
experiment. | [
1,
1,
0,
0,
0,
0
] | [
"Quantitative Biology",
"Computer Science"
] |
Title: Design and implementation of lighting control system using battery-less wireless human detection sensor networks,
Abstract: Artificial lighting is responsible for a large portion of total energy
consumption and has great potential for energy saving. This paper designs an
LED light control algorithm based on users' localization using multiple
battery-less binary human detection sensors. The proposed lighting control
system focuses on reducing office lighting energy consumption and satisfying
users' illumination requirement. Most current lighting control systems use
infrared human detection sensors, but the poor detection probability,
especially for a static user, makes it difficult to realize comfortable and
effective lighting control. To improve the detection probability of each
sensor, we proposed to locate sensors as close to each user as possible by
using a battery-less wireless sensor network, in which all sensors can be
placed freely in the space with high energy stability. We also proposed to use
a multi-sensor-based user localization algorithm to capture user's position
more accurately and realize fine lighting control which works even with static
users. The system is actually implemented in an indoor office environment in a
pilot project. A verification experiment is conducted by measuring the
practical illumination and power consumption. The performance agrees with
design expectations. It shows that the proposed LED lighting control system
reduces the energy consumption significantly, 57% compared to the batch control
scheme, and satisfies user's illumination requirement with 100% probability. | [
1,
0,
0,
0,
0,
0
] | [
"Computer Science"
] |
Title: Propagation of regularity for the MHD system in optimal Sobolev space,
Abstract: We study the problem of propagation of regularity of solutions to the
incompressible viscous non-resistive magneto-hydrodynamics system. According to
scaling, the Sobolev space $H^{\frac n2-1}(\mathbb R^n)\times H^{\frac
n2}(\mathbb R^n)$ is critical for the system. We show that if a weak solution
$(u(t),b(t))$ is in $H^{s}(\mathbb R^n)\times H^{s+1}(\mathbb R^n)$ with
$s>\frac n2-1$ at a certain time $t_0$, then it will stay in the space for a
short time, provided the initial velocity $u(0)\in H^s(\mathbb R^n)$. In the
case that the uniqueness of weak solution in $H^{s}(\mathbb R^n)\times
H^{s+1}(\mathbb R^n)$ is known, the assumption of $u(0)\in H^s(\mathbb R^n)$ is
not necessary. | [
0,
1,
1,
0,
0,
0
] | [
"Mathematics",
"Physics"
] |
Title: Universal Scaling Laws for Correlation Spreading in Quantum Systems with Short- and Long-Range Interactions,
Abstract: We study the spreading of information in a wide class of quantum systems,
with variable-range interactions. We show that, after a quench, it generally
features a double structure, whose scaling laws are related to a set of
universal microscopic exponents that we determine. When the system supports
excitations with a finite maximum velocity, the spreading shows a twofold
ballistic behavior. While the correlation edge spreads with a velocity equal to
twice the maximum group velocity, the dominant correlation maxima propagate
with a different velocity that we derive. When the maximum group velocity
diverges, as realizable with long-range interactions, the correlation edge
features a slower-than-ballistic motion. The motion of the maxima is, instead,
either faster-than-ballistic, for gapless systems, or ballistic, for gapped
systems. The phenomenology that we unveil here provides a unified framework,
which encompasses existing experimental observations with ultracold atoms and
ions. It also paves the way to simple extensions of those experiments to
observe the structures we describe in their full generality. | [
0,
1,
0,
0,
0,
0
] | [
"Physics"
] |
Title: Examples of plane rational curves with two Galois points in positive characteristic,
Abstract: We present four new examples of plane rational curves with two Galois points
in positive characteristic, and determine the number of Galois points for three
of them. Our results are related to a problem on projective linear groups. | [
0,
0,
1,
0,
0,
0
] | [
"Mathematics"
] |
Title: Optimal Kullback-Leibler Aggregation in Mixture Density Estimation by Maximum Likelihood,
Abstract: We study the maximum likelihood estimator of density of $n$ independent
observations, under the assumption that it is well approximated by a mixture
with a large number of components. The main focus is on statistical properties
with respect to the Kullback-Leibler loss. We establish risk bounds taking the
form of sharp oracle inequalities both in deviation and in expectation. A
simple consequence of these bounds is that the maximum likelihood estimator
attains the optimal rate $((\log K)/n)^{1/2}$, up to a possible logarithmic
correction, in the problem of convex aggregation when the number $K$ of
components is larger than $n^{1/2}$. More importantly, under the additional
assumption that the Gram matrix of the components satisfies the compatibility
condition, the obtained oracle inequalities yield the optimal rate in the
sparsity scenario. That is, if the weight vector is (nearly) $D$-sparse, we get
the rate $(D\log K)/n$. As a natural complement to our oracle inequalities, we
introduce the notion of nearly-$D$-sparse aggregation and establish matching
lower bounds for this type of aggregation. | [
0,
0,
1,
1,
0,
0
] | [
"Statistics",
"Mathematics"
] |
Title: Hierarchical Reinforcement Learning: Approximating Optimal Discounted TSP Using Local Policies,
Abstract: In this work, we provide theoretical guarantees for reward decomposition in
deterministic MDPs. Reward decomposition is a special case of Hierarchical
Reinforcement Learning, that allows one to learn many policies in parallel and
combine them into a composite solution. Our approach builds on mapping this
problem into a Reward Discounted Traveling Salesman Problem, and then deriving
approximate solutions for it. In particular, we focus on approximate solutions
that are local, i.e., solutions that only observe information about the current
state. Local policies are easy to implement and do not require substantial
computational resources as they do not perform planning. While local
deterministic policies, like Nearest Neighbor, are being used in practice for
hierarchical reinforcement learning, we propose three stochastic policies that
guarantee better performance than any deterministic policy. | [
0,
0,
0,
1,
0,
0
] | [
"Computer Science",
"Mathematics"
] |
Title: End-to-End Musical Key Estimation Using a Convolutional Neural Network,
Abstract: We present an end-to-end system for musical key estimation, based on a
convolutional neural network. The proposed system not only out-performs
existing key estimation methods proposed in the academic literature; it is also
capable of learning a unified model for diverse musical genres that performs
comparably to existing systems specialised for specific genres. Our experiments
confirm that different genres do differ in their interpretation of tonality,
and thus a system tuned e.g. for pop music performs subpar on pieces of
electronic music. They also reveal that such cross-genre setups evoke specific
types of error (predicting the relative or parallel minor). However, using the
data-driven approach proposed in this paper, we can train models that deal with
multiple musical styles adequately, and without major losses in accuracy. | [
1,
0,
0,
0,
0,
0
] | [
"Computer Science",
"Quantitative Biology"
] |
Title: Approximate Optimal Designs for Multivariate Polynomial Regression,
Abstract: We introduce a new approach aiming at computing approximate optimal designs
for multivariate polynomial regressions on compact (semi-algebraic) design
spaces. We use the moment-sum-of-squares hierarchy of semidefinite programming
problems to solve numerically the approximate optimal design problem. The
geometry of the design is recovered via semidefinite programming duality
theory. This article shows that the hierarchy converges to the approximate
optimal design as the order of the hierarchy increases. Furthermore, we provide
a dual certificate ensuring finite convergence of the hierarchy and showing
that the approximate optimal design can be computed numerically with our
method. As a byproduct, we revisit the equivalence theorem of the experimental
design theory: it is linked to the Christoffel polynomial and it characterizes
finite convergence of the moment-sum-of-square hierarchies. | [
0,
0,
1,
1,
0,
0
] | [
"Mathematics",
"Statistics",
"Computer Science"
] |
Title: Large-scale Datasets: Faces with Partial Occlusions and Pose Variations in the Wild,
Abstract: Face detection methods have relied on face datasets for training. However,
existing face datasets tend to be in small scales for face learning in both
constrained and unconstrained environments. In this paper, we first introduce
our large-scale image datasets, Large-scale Labeled Face (LSLF) and noisy
Large-scale Labeled Non-face (LSLNF). Our LSLF dataset consists of a large
number of unconstrained multi-view and partially occluded faces. The faces have
many variations in color and grayscale, image quality, image resolution, image
illumination, image background, image illusion, human face, cartoon face,
facial expression, light and severe partial facial occlusion, make up, gender,
age, and race. Many of these faces are partially occluded with accessories such
as tattoos, hats, glasses, sunglasses, hands, hair, beards, scarves,
microphones, or other objects or persons. The LSLF dataset is currently the
largest labeled face image dataset in the literature in terms of the number of
labeled images and the number of individuals compared to other existing labeled
face image datasets. Second, we introduce our CrowedFaces and CrowedNonFaces
image datasets. The crowedFaces and CrowedNonFaces datasets include faces and
non-faces images from crowed scenes. These datasets essentially aim for
researchers to provide a large number of training examples with many variations
for large scale face learning and face recognition tasks. | [
1,
0,
0,
0,
0,
0
] | [
"Computer Science"
] |
Title: Compressive Sensing via Convolutional Factor Analysis,
Abstract: We solve the compressive sensing problem via convolutional factor analysis,
where the convolutional dictionaries are learned {\em in situ} from the
compressed measurements. An alternating direction method of multipliers (ADMM)
paradigm for compressive sensing inversion based on convolutional factor
analysis is developed. The proposed algorithm provides reconstructed images as
well as features, which can be directly used for recognition ($e.g.$,
classification) tasks. When a deep (multilayer) model is constructed, a
stochastic unpooling process is employed to build a generative model. During
reconstruction and testing, we project the upper layer dictionary to the data
level and only a single layer deconvolution is required. We demonstrate that
using $\sim30\%$ (relative to pixel numbers) compressed measurements, the
proposed model achieves the classification accuracy comparable to the original
data on MNIST. We also observe that when the compressed measurements are very
limited ($e.g.$, $<10\%$), the upper layer dictionary can provide better
reconstruction results than the bottom layer. | [
1,
0,
0,
1,
0,
0
] | [
"Computer Science",
"Statistics",
"Mathematics"
] |
Title: Multi-Dialect Speech Recognition With A Single Sequence-To-Sequence Model,
Abstract: Sequence-to-sequence models provide a simple and elegant solution for
building speech recognition systems by folding separate components of a typical
system, namely acoustic (AM), pronunciation (PM) and language (LM) models into
a single neural network. In this work, we look at one such sequence-to-sequence
model, namely listen, attend and spell (LAS), and explore the possibility of
training a single model to serve different English dialects, which simplifies
the process of training multi-dialect systems without the need for separate AM,
PM and LMs for each dialect. We show that simply pooling the data from all
dialects into one LAS model falls behind the performance of a model fine-tuned
on each dialect. We then look at incorporating dialect-specific information
into the model, both by modifying the training targets by inserting the dialect
symbol at the end of the original grapheme sequence and also feeding a 1-hot
representation of the dialect information into all layers of the model.
Experimental results on seven English dialects show that our proposed system is
effective in modeling dialect variations within a single LAS model,
outperforming a LAS model trained individually on each of the seven dialects by
3.1 ~ 16.5% relative. | [
1,
0,
0,
0,
0,
0
] | [
"Computer Science"
] |
Title: What is a hierarchically hyperbolic space?,
Abstract: The first part of this survey is a heuristic, non-technical discussion of
what an HHS is, and the aim is to provide a good mental picture both to those
actively doing research on HHSs and to those who only seek a basic
understanding out of pure curiosity. It can be read independently of the second
part, which is a detailed technical discussion of the axioms and the main tools
to deal with HHSs. | [
0,
0,
1,
0,
0,
0
] | [
"Mathematics"
] |
Title: Neural networks and rational functions,
Abstract: Neural networks and rational functions efficiently approximate each other. In
more detail, it is shown here that for any ReLU network, there exists a
rational function of degree $O(\text{polylog}(1/\epsilon))$ which is
$\epsilon$-close, and similarly for any rational function there exists a ReLU
network of size $O(\text{polylog}(1/\epsilon))$ which is $\epsilon$-close. By
contrast, polynomials need degree $\Omega(\text{poly}(1/\epsilon))$ to
approximate even a single ReLU. When converting a ReLU network to a rational
function as above, the hidden constants depend exponentially on the number of
layers, which is shown to be tight; in other words, a compositional
representation can be beneficial even for rational functions. | [
1,
0,
0,
1,
0,
0
] | [
"Computer Science",
"Mathematics"
] |
Title: Local Structure Theorems for Erdos Renyi Graphs and their Algorithmic Application,
Abstract: We analyze some local properties of sparse Erdos-Renyi graphs, where $d(n)/n$
is the edge probability. In particular we study the behavior of very short
paths. For $d(n)=n^{o(1)}$ we show that $G(n,d(n)/n)$ has asymptotically almost
surely (a.a.s.~) bounded local treewidth and therefore is a.a.s.~nowhere dense.
We also discover a new and simpler proof that $G(n,d/n)$ has a.a.s.~bounded
expansion for constant~$d$. The local structure of sparse Erdos-Renyi Gaphs is
very special: The $r$-neighborhood of a vertex is a tree with some additional
edges, where the probability that there are $m$ additional edges decreases
with~$m$. This implies efficient algorithms for subgraph isomorphism, in
particular for finding subgraphs with small diameter. Finally we note that
experiments suggest that preferential attachment graphs might have similar
properties after deleting a small number of vertices. | [
1,
0,
0,
0,
0,
0
] | [
"Computer Science",
"Mathematics"
] |
Title: Automatic Pill Reminder for Easy Supervision,
Abstract: In this paper we present a working model of an automatic pill reminder and
dispenser setup that can alleviate irregularities in taking prescribed dosage
of medicines at the right time dictated by the medical practitioner and switch
from approaches predominantly dependent on human memory to automation with
negligible supervision, thus relieving persons from error-prone tasks of giving
wrong medicine at the wrong time in the wrong amount. | [
1,
0,
0,
0,
0,
0
] | [
"Computer Science"
] |
Title: Unpredictable sequences and Poincaré chaos,
Abstract: To make research of chaos more friendly with discrete equations, we introduce
the concept of an unpredictable sequence as a specific unpredictable function
on the set of integers. It is convenient to be verified as a solution of a
discrete equation. This is rigorously proved in this paper for quasilinear
systems, and we demonstrate the result numerically for linear systems in the
critical case with respect to the stability of the origin. The completed
research contributes to the theory of chaos as well as to the theory of
discrete equations, considering unpredictable solutions. | [
0,
1,
0,
0,
0,
0
] | [
"Mathematics",
"Physics"
] |
Title: Lumping of Degree-Based Mean Field and Pair Approximation Equations for Multi-State Contact Processes,
Abstract: Contact processes form a large and highly interesting class of dynamic
processes on networks, including epidemic and information spreading. While
devising stochastic models of such processes is relatively easy, analyzing them
is very challenging from a computational point of view, particularly for large
networks appearing in real applications. One strategy to reduce the complexity
of their analysis is to rely on approximations, often in terms of a set of
differential equations capturing the evolution of a random node, distinguishing
nodes with different topological contexts (i.e., different degrees of different
neighborhoods), like degree-based mean field (DBMF), approximate master
equation (AME), or pair approximation (PA). The number of differential
equations so obtained is typically proportional to the maximum degree kmax of
the network, which is much smaller than the size of the master equation of the
underlying stochastic model, yet numerically solving these equations can still
be problematic for large kmax. In this paper, we extend AME and PA, which has
been proposed only for the binary state case, to a multi-state setting and
provide an aggregation procedure that clusters together nodes having similar
degrees, treating those in the same cluster as indistinguishable, thus reducing
the number of equations while preserving an accurate description of global
observables of interest. We also provide an automatic way to build such
equations and to identify a small number of degree clusters that give accurate
results. The method is tested on several case studies, where it shows a high
level of compression and a reduction of computational time of several orders of
magnitude for large networks, with minimal loss in accuracy. | [
1,
1,
0,
0,
0,
0
] | [
"Computer Science",
"Mathematics"
] |
Title: VLocNet++: Deep Multitask Learning for Semantic Visual Localization and Odometry,
Abstract: Semantic understanding and localization are fundamental enablers of robot
autonomy that have for the most part been tackled as disjoint problems. While
deep learning has enabled recent breakthroughs across a wide spectrum of scene
understanding tasks, its applicability to state estimation tasks has been
limited due to the direct formulation that renders it incapable of encoding
scene-specific constrains. In this work, we propose the VLocNet++ architecture
that employs a multitask learning approach to exploit the inter-task
relationship between learning semantics, regressing 6-DoF global pose and
odometry, for the mutual benefit of each of these tasks. Our network overcomes
the aforementioned limitation by simultaneously embedding geometric and
semantic knowledge of the world into the pose regression network. We propose a
novel adaptive weighted fusion layer to aggregate motion-specific temporal
information and to fuse semantic features into the localization stream based on
region activations. Furthermore, we propose a self-supervised warping technique
that uses the relative motion to warp intermediate network representations in
the segmentation stream for learning consistent semantics. Finally, we
introduce a first-of-a-kind urban outdoor localization dataset with pixel-level
semantic labels and multiple loops for training deep networks. Extensive
experiments on the challenging Microsoft 7-Scenes benchmark and our DeepLoc
dataset demonstrate that our approach exceeds the state-of-the-art
outperforming local feature-based methods while simultaneously performing
multiple tasks and exhibiting substantial robustness in challenging scenarios. | [
1,
0,
0,
0,
0,
0
] | [
"Computer Science",
"Quantitative Biology"
] |
Title: On Decidability of the Ordered Structures of Numbers,
Abstract: The ordered structures of natural, integer, rational and real numbers are
studied here. It is known that the theories of these numbers in the language of
order are decidable and finitely axiomatizable. Also, their theories in the
language of order and addition are decidable and infinitely axiomatizable. For
the language of order and multiplication, it is known that the theories of
$\mathbb{N}$ and $\mathbb{Z}$ are not decidable (and so not axiomatizable by
any computably enumerable set of sentences). By Tarski's theorem, the
multiplicative ordered structure of $\mathbb{R}$ is decidable also; here we
prove this result directly and present an axiomatization. The structure of
$\mathbb{Q}$ in the language of order and multiplication seems to be missing in
the literature; here we show the decidability of its theory by the technique of
quantifier elimination and after presenting an infinite axiomatization for this
structure we prove that it is not finitely axiomatizable. | [
1,
0,
1,
0,
0,
0
] | [
"Mathematics",
"Computer Science"
] |
Title: Finite $p$-groups of conjugate type $\{ 1, p^3 \}$,
Abstract: We classify finite $p$-groups, upto isoclinism, which have only two conjugacy
class sizes $1$ and $p^3$. It turns out that the nilpotency class of such
groups is $2$. | [
0,
0,
1,
0,
0,
0
] | [
"Mathematics"
] |
Title: Betting on Quantum Objects,
Abstract: Dutch book arguments have been applied to beliefs about the outcomes of
measurements of quantum systems, but not to beliefs about quantum objects prior
to measurement. In this paper, we prove a quantum version of the probabilists'
Dutch book theorem that applies to both sorts of beliefs: roughly, if ideal
beliefs are given by vector states, all and only Born-rule probabilities avoid
Dutch books. This theorem and associated results have implications for
operational and realist interpretations of the logic of a Hilbert lattice. In
the latter case, we show that the defenders of the eigenstate-value orthodoxy
face a trilemma. Those who favor vague properties avoid the trilemma, admitting
all and only those beliefs about quantum objects that avoid Dutch books. | [
0,
1,
0,
0,
0,
0
] | [
"Physics",
"Mathematics"
] |
Title: Electron-Muon Ranger: hardware characterization,
Abstract: The Electron-Muon Ranger (EMR) is a fully-active tracking-calorimeter in
charge of the electron background rejection downstream of the cooling channel
at the international Muon Ionization Cooling Experiment. It consists of 2832
plastic scintillator bars segmented in 48 planes in an X-Y arrangement and uses
particle range as its main variable to tag muons and discriminate electrons. An
array of analyses were conducted to characterize the hardware of the EMR and
determine whether the detector performs to specifications. The clear fibres
coming from the bars were shown to transmit the desired amount of light, and
only four dead channels were identified in the electronics. Two channels had
indubitably been mismatched during assembly and the DAQ channel map was
subsequently corrected. The level of crosstalk is within acceptable values for
the type of multi-anode photomultiplier used with an average of
$0.20\pm0.03\,\%$ probability of occurrence in adjacent channels and a mean
amplitude equivalent to $4.5\pm0.1\,\%$ of the primary signal intensity. The
efficiency of the signal acquisition, defined as the probability of recording a
signal in a plane when a particle goes through it in beam conditions, reached
$99.73\pm0.02\,\%$. | [
0,
1,
0,
0,
0,
0
] | [
"Physics"
] |
Title: Shallow Updates for Deep Reinforcement Learning,
Abstract: Deep reinforcement learning (DRL) methods such as the Deep Q-Network (DQN)
have achieved state-of-the-art results in a variety of challenging,
high-dimensional domains. This success is mainly attributed to the power of
deep neural networks to learn rich domain representations for approximating the
value function or policy. Batch reinforcement learning methods with linear
representations, on the other hand, are more stable and require less hyper
parameter tuning. Yet, substantial feature engineering is necessary to achieve
good results. In this work we propose a hybrid approach -- the Least Squares
Deep Q-Network (LS-DQN), which combines rich feature representations learned by
a DRL algorithm with the stability of a linear least squares method. We do this
by periodically re-training the last hidden layer of a DRL network with a batch
least squares update. Key to our approach is a Bayesian regularization term for
the least squares update, which prevents over-fitting to the more recent data.
We tested LS-DQN on five Atari games and demonstrate significant improvement
over vanilla DQN and Double-DQN. We also investigated the reasons for the
superior performance of our method. Interestingly, we found that the
performance improvement can be attributed to the large batch size used by the
LS method when optimizing the last layer. | [
1,
0,
0,
1,
0,
0
] | [
"Computer Science",
"Statistics"
] |
Title: Survey on Additive Manufacturing, Cloud 3D Printing and Services,
Abstract: Cloud Manufacturing (CM) is the concept of using manufacturing resources in a
service oriented way over the Internet. Recent developments in Additive
Manufacturing (AM) are making it possible to utilise resources ad-hoc as
replacement for traditional manufacturing resources in case of spontaneous
problems in the established manufacturing processes. In order to be of use in
these scenarios the AM resources must adhere to a strict principle of
transparency and service composition in adherence to the Cloud Computing (CC)
paradigm. With this review we provide an overview over CM, AM and relevant
domains as well as present the historical development of scientific research in
these fields, starting from 2002. Part of this work is also a meta-review on
the domain to further detail its development and structure. | [
1,
0,
0,
0,
0,
0
] | [
"Computer Science"
] |
Title: Barnacles and Gravity,
Abstract: Theories with more than one vacuum allow quantum transitions between them,
which may proceed via bubble nucleation; theories with more than two vacua
posses additional decay modes in which the wall of a bubble may further decay.
The instantons which mediate such a process have $O(3)$ symmetry (in four
dimensions, rather than the usual $O(4)$ symmetry of homogeneous vacuum decay),
and have been called `barnacles'; previously they have been studied in flat
space, in the thin wall limit, and this paper extends the analysis to include
gravity. It is found that there are regions of parameter space in which, given
an initial bubble, barnacles are the favoured subsequent decay process, and
that the inclusion of gravity can enlarge this region. The relation to other
heterogeneous vacuum decay scenarios, as well as some of the phenomenological
implications of barnacles are briefly discussed. | [
0,
1,
0,
0,
0,
0
] | [
"Physics"
] |
Title: Thresholding Bandit for Dose-ranging: The Impact of Monotonicity,
Abstract: We analyze the sample complexity of the thresholding bandit problem, with and
without the assumption that the mean values of the arms are increasing. In each
case, we provide a lower bound valid for any risk $\delta$ and any
$\delta$-correct algorithm; in addition, we propose an algorithm whose sample
complexity is of the same order of magnitude for small risks. This work is
motivated by phase 1 clinical trials, a practically important setting where the
arm means are increasing by nature, and where no satisfactory solution is
available so far. | [
0,
0,
1,
1,
0,
0
] | [
"Statistics",
"Mathematics",
"Quantitative Biology"
] |
Title: A Univariate Bound of Area Under ROC,
Abstract: Area under ROC (AUC) is an important metric for binary classification and
bipartite ranking problems. However, it is difficult to directly optimizing AUC
as a learning objective, so most existing algorithms are based on optimizing a
surrogate loss to AUC. One significant drawback of these surrogate losses is
that they require pairwise comparisons among training data, which leads to slow
running time and increasing local storage for online learning. In this work, we
describe a new surrogate loss based on a reformulation of the AUC risk, which
does not require pairwise comparison but rankings of the predictions. We
further show that the ranking operation can be avoided, and the learning
objective obtained based on this surrogate enjoys linear complexity in time and
storage. We perform experiments to demonstrate the effectiveness of the online
and batch algorithms for AUC optimization based on the proposed surrogate loss. | [
0,
0,
0,
1,
0,
0
] | [
"Computer Science",
"Statistics"
] |
Title: Evidences against cuspy dark matter halos in large galaxies,
Abstract: We develop and apply new techniques in order to uncover galaxy rotation
curves (RC) systematics. Considering that an ideal dark matter (DM) profile
should yield RCs that have no bias towards any particular radius, we find that
the Burkert DM profile satisfies the test, while the Navarro-Frenk-While (NFW)
profile has a tendency of better fitting the region between one and two disc
scale lengths than the inner disc scale length region. Our sample indicates
that this behaviour happens to more than 75% of the galaxies fitted with an NFW
halo. Also, this tendency does not weaken by considering "large" galaxies, for
instance those with $M_*\gtrsim 10^{10} M_\odot$. Besides the tests on the
homogeneity of the fits, we also use a sample of 62 galaxies of diverse types
to perform tests on the quality of the overall fit of each galaxy, and to
search for correlations with stellar mass, gas mass and the disc scale length.
In particular, we find that only 13 galaxies are better fitted by the NFW halo;
and that even for the galaxies with $M_* \gtrsim 10^{10} M_\odot$ the Burkert
profile either fits as good as, or better than, the NFW profile. This result is
relevant since different baryonic effects important for the smaller galaxies,
like supernova feedback and dynamical friction from baryonic clumps, indicate
that at such large stellar masses the NFW profile should be preferred over the
Burkert profile. Hence, our results either suggest a new baryonic effect or a
change of the dark matter physics. | [
0,
1,
0,
0,
0,
0
] | [
"Physics"
] |
Title: A Hybrid Framework for Multi-Vehicle Collision Avoidance,
Abstract: With the recent surge of interest in UAVs for civilian services, the
importance of developing tractable multi-agent analysis techniques that provide
safety and performance guarantees have drastically increased. Hamilton-Jacobi
(HJ) reachability has successfully provided these guarantees to small-scale
systems and is flexible in terms of system dynamics. However, the exponential
complexity scaling of HJ reachability with respect to system dimension prevents
its direct application to larger-scale problems where the number of vehicles is
greater than two. In this paper, we propose a collision avoidance algorithm
using a hybrid framework for N+1 vehicles through higher-level control logic
given any N-vehicle collision avoidance algorithm. Our algorithm conservatively
approximates a guaranteed-safe region in the joint state space of the N+1
vehicles and produces a safety-preserving controller. In addition, our
algorithm does not incur significant additional computation cost. We
demonstrate our proposed method in simulation. | [
0,
0,
1,
0,
0,
0
] | [
"Computer Science",
"Mathematics"
] |
Title: On Topologized Fundamental Groups with Small Loop Transfer Viewpoints,
Abstract: In this paper, by introducing some kind of small loop transfer spaces at a
point, we study the behavior of topologized fundamental groups with the
compact-open topology and the whisker topology, $\pi_{1}^{qtop}(X,x_{0})$ and
$\pi_{1}^{wh}(X,x_{0})$, respectively. In particular, we give necessary or
sufficient conditions for coincidence and being topological group of these two
topologized fundamental groups. Finally, we give some examples to show that the
reverse of some of these implications do not hold, in general. | [
0,
0,
1,
0,
0,
0
] | [
"Mathematics"
] |
Title: Polish Topologies for Graph Products of Groups,
Abstract: We give strong necessary conditions on the admissibility of a Polish group
topology for an arbitrary graph product of groups $G(\Gamma, G_a)$, and use
them to give a characterization modulo a finite set of nodes. As a corollary,
we give a complete characterization in case all the factor groups $G_a$ are
countable. | [
0,
0,
1,
0,
0,
0
] | [
"Mathematics"
] |
Title: Analytic Combinatorics in Several Variables: Effective Asymptotics and Lattice Path Enumeration,
Abstract: The field of analytic combinatorics, which studies the asymptotic behaviour
of sequences through analytic properties of their generating functions, has led
to the development of deep and powerful tools with applications across
mathematics and the natural sciences. In addition to the now classical
univariate theory, recent work in the study of analytic combinatorics in
several variables (ACSV) has shown how to derive asymptotics for the
coefficients of certain D-finite functions represented by diagonals of
multivariate rational functions. We give a pedagogical introduction to the
methods of ACSV from a computer algebra viewpoint, developing rigorous
algorithms and giving the first complexity results in this area under
conditions which are broadly satisfied. Furthermore, we give several new
applications of ACSV to the enumeration of lattice walks restricted to certain
regions. In addition to proving several open conjectures on the asymptotics of
such walks, a detailed study of lattice walk models with weighted steps is
undertaken. | [
1,
0,
0,
0,
0,
0
] | [
"Mathematics",
"Computer Science"
] |
Title: A Transferable Pedestrian Motion Prediction Model for Intersections with Different Geometries,
Abstract: This paper presents a novel framework for accurate pedestrian intent
prediction at intersections. Given some prior knowledge of the curbside
geometry, the presented framework can accurately predict pedestrian
trajectories, even in new intersections that it has not been trained on. This
is achieved by making use of the contravariant components of trajectories in
the curbside coordinate system, which ensures that the transformation of
trajectories across intersections is affine, regardless of the curbside
geometry. Our method is based on the Augmented Semi Nonnegative Sparse Coding
(ASNSC) formulation and we use that as a baseline to show improvement in
prediction performance on real pedestrian datasets collected at two
intersections in Cambridge, with distinctly different curbside and crosswalk
geometries. We demonstrate a 7.2% improvement in prediction accuracy in the
case of same train and test intersections. Furthermore, we show a comparable
prediction performance of TASNSC when trained and tested in different
intersections with the baseline, trained and tested on the same intersection. | [
1,
0,
0,
1,
0,
0
] | [
"Computer Science",
"Statistics"
] |
Title: Generating GraphQL-Wrappers for REST(-like) APIs,
Abstract: GraphQL is a query language and thereupon-based paradigm for implementing web
Application Programming Interfaces (APIs) for client-server interactions. Using
GraphQL, clients define precise, nested data-requirements in typed queries,
which are resolved by servers against (possibly multiple) backend systems, like
databases, object storages, or other APIs. Clients receive only the data they
care about, in a single request. However, providers of existing REST(-like)
APIs need to implement additional GraphQL interfaces to enable these
advantages. We here assess the feasibility of automatically generating GraphQL
wrappers for existing REST(-like) APIs. A wrapper, upon receiving GraphQL
queries, translates them to requests against the target API. We discuss the
challenges for creating such wrappers, including dealing with data sanitation,
authentication, or handling nested queries. We furthermore present a
prototypical implementation of OASGraph. OASGraph takes as input an OpenAPI
Specification (OAS) describing an existing REST(-like) web API and generates a
GraphQL wrapper for it. We evaluate OASGraph by running it, as well as an
existing open source alternative, against 959 publicly available OAS. This
experiment shows that OASGraph outperforms the existing alternative and is able
to create a GraphQL wrapper for 89.5% of the APIs -- however, with limitations
in many cases. A subsequent analysis of errors and warnings produced by
OASGraph shows that missing or ambiguous information in the assessed OAS
hinders creating complete wrappers. Finally, we present a use case of the IBM
Watson Language Translator API that shows that small changes to an OAS allow
OASGraph to generate more idiomatic and more expressive GraphQL wrappers. | [
1,
0,
0,
0,
0,
0
] | [
"Computer Science"
] |
Title: The growth of carbon chains in IRC+10216 mapped with ALMA,
Abstract: Linear carbon chains are common in various types of astronomical molecular
sources. Possible formation mechanisms involve both bottom-up and top-down
routes. We have carried out a combined observational and modeling study of the
formation of carbon chains in the C-star envelope IRC+10216, where the
polymerization of acetylene and hydrogen cyanide induced by ultraviolet photons
can drive the formation of linear carbon chains of increasing length. We have
used ALMA to map the emission of 3 mm rotational lines of the hydrocarbon
radicals C2H, C4H, and C6H, and the CN-containing species CN, C3N, HC3N, and
HC5N with an angular resolution of 1". The spatial distribution of all these
species is a hollow, 5-10" wide, spherical shell located at a radius of 10-20"
from the star, with no appreciable emission close to the star. Our observations
resolve the broad shell of carbon chains into thinner sub-shells which are 1-2"
wide and not fully concentric, indicating that the mass loss process has been
discontinuous and not fully isotropic. The radial distributions of the species
mapped reveal subtle differences: while the hydrocarbon radicals have very
similar radial distributions, the CN-containing species show more diverse
distributions, with HC3N appearing earlier in the expansion and the radical CN
extending later than the rest of the species. The observed morphology can be
rationalized by a chemical model in which the growth of polyynes is mainly
produced by rapid gas-phase chemical reactions of C2H and C4H radicals with
unsaturated hydrocarbons, while cyanopolyynes are mainly formed from polyynes
in gas-phase reactions with CN and C3N radicals. | [
0,
1,
0,
0,
0,
0
] | [
"Physics"
] |
Title: Fast and Lightweight Rate Control for Onboard Predictive Coding of Hyperspectral Images,
Abstract: Predictive coding is attractive for compression of hyperspecral images
onboard of spacecrafts in light of the excellent rate-distortion performance
and low complexity of recent schemes. In this letter we propose a rate control
algorithm and integrate it in a lossy extension to the CCSDS-123 lossless
compression recommendation. The proposed rate algorithm overhauls our previous
scheme by being orders of magnitude faster and simpler to implement, while
still providing the same accuracy in terms of output rate and comparable or
better image quality. | [
1,
0,
0,
0,
0,
0
] | [
"Computer Science",
"Physics"
] |
Title: Quantum-continuum calculation of the surface states and electrical response of silicon in solution,
Abstract: A wide range of electrochemical reactions of practical importance occur at
the interface between a semiconductor and an electrolyte. We present an
embedded density-functional theory method using the recently released
self-consistent continuum solvation (SCCS) approach to study these interfaces.
In this model, a quantum description of the surface is incorporated into a
continuum representation of the bending of the bands within the electrode. The
model is applied to understand the electrical response of silicon electrodes in
solution, providing microscopic insights into the low-voltage region, where
surface states determine the electrification of the semiconductor electrode. | [
0,
1,
0,
0,
0,
0
] | [
"Physics",
"Chemistry"
] |
Title: Laser electron acceleration on curved surfaces,
Abstract: Electron acceleration by relativistically intense laser beam propagating
along a curved surface allows to split softly the accelerated electron bunch
and the laser beam. The presence of a curved surface allows to switch an
adiabatic invariant of electrons in the wave instantly leaving the gained
energy to the particles. The efficient acceleration is provided by the presence
of strong transient quasistationary fields in the interaction region and a long
efficient acceleration length. The curvature of the surface allows to select
the accelerated particles and provides their narrow angular distribution. The
mechanism at work is explicitly demonstrated in theoretical models and
experiments. | [
0,
1,
0,
0,
0,
0
] | [
"Physics"
] |
Title: Thermalization after holographic bilocal quench,
Abstract: We study thermalization in the holographic (1+1)-dimensional CFT after
simultaneous generation of two high-energy excitations in the antipodal points
on the circle. The holographic picture of such quantum quench is the creation
of BTZ black hole from a collision of two massless particles. We perform
holographic computation of entanglement entropy and mutual information in the
boundary theory and analyze their evolution with time. We show that
equilibration of the entanglement in the regions which contained one of the
initial excitations is generally similar to that in other holographic quench
models, but with some important distinctions. We observe that entanglement
propagates along a sharp effective light cone from the points of initial
excitations on the boundary. The characteristics of entanglement propagation in
the global quench models such as entanglement velocity and the light cone
velocity also have a meaning in the bilocal quench scenario. We also observe
the loss of memory about the initial state during the equilibration process. We
find that the memory loss reflects on the time behavior of the entanglement
similarly to the global quench case, and it is related to the universal linear
growth of entanglement, which comes from the interior of the forming black
hole. We also analyze general two-point correlation functions in the framework
of the geodesic approximation, focusing on the study of the late time behavior. | [
0,
1,
0,
0,
0,
0
] | [
"Physics"
] |
Title: Endpoint Sobolev and BV continuity for maximal operators,
Abstract: In this paper we investigate some questions related to the continuity of
maximal operators in $W^{1,1}$ and $BV$ spaces, complementing some well-known
boundedness results. Letting $\widetilde M$ be the one-dimensional uncentered
Hardy-Littlewood maximal operator, we prove that the map $f \mapsto
\big(\widetilde Mf\big)'$ is continuous from $W^{1,1}(\mathbb{R})$ to
$L^1(\mathbb{R})$. In the discrete setting, we prove that $\widetilde M:
BV(\mathbb{Z}) \to BV(\mathbb{Z})$ is also continuous. For the one-dimensional
fractional Hardy-Littlewood maximal operator, we prove by means of
counterexamples that the corresponding continuity statements do not hold, both
in the continuous and discrete settings, and for the centered and uncentered
versions. | [
0,
0,
1,
0,
0,
0
] | [
"Mathematics"
] |
Title: Self-paced Convolutional Neural Network for Computer Aided Detection in Medical Imaging Analysis,
Abstract: Tissue characterization has long been an important component of Computer
Aided Diagnosis (CAD) systems for automatic lesion detection and further
clinical planning. Motivated by the superior performance of deep learning
methods on various computer vision problems, there has been increasing work
applying deep learning to medical image analysis. However, the development of a
robust and reliable deep learning model for computer-aided diagnosis is still
highly challenging due to the combination of the high heterogeneity in the
medical images and the relative lack of training samples. Specifically,
annotation and labeling of the medical images is much more expensive and
time-consuming than other applications and often involves manual labor from
multiple domain experts. In this work, we propose a multi-stage, self-paced
learning framework utilizing a convolutional neural network (CNN) to classify
Computed Tomography (CT) image patches. The key contribution of this approach
is that we augment the size of training samples by refining the unlabeled
instances with a self-paced learning CNN. By implementing the framework on high
performance computing servers including the NVIDIA DGX1 machine, we obtained
the experimental result, showing that the self-pace boosted network
consistently outperformed the original network even with very scarce manual
labels. The performance gain indicates that applications with limited training
samples such as medical image analysis can benefit from using the proposed
framework. | [
1,
0,
0,
1,
0,
0
] | [
"Computer Science",
"Quantitative Biology"
] |
Title: PS-DBSCAN: An Efficient Parallel DBSCAN Algorithm Based on Platform Of AI (PAI),
Abstract: We present PS-DBSCAN, a communication efficient parallel DBSCAN algorithm
that combines the disjoint-set data structure and Parameter Server framework in
Platform of AI (PAI). Since data points within the same cluster may be
distributed over different workers which result in several disjoint-sets,
merging them incurs large communication costs. In our algorithm, we employ a
fast global union approach to union the disjoint-sets to alleviate the
communication burden. Experiments over the datasets of different scales
demonstrate that PS-DBSCAN outperforms the PDSDBSCAN with 2-10 times speedup on
communication efficiency.
We have released our PS-DBSCAN in an algorithm platform called Platform of AI
(PAI - this https URL) in Alibaba Cloud. We have also
demonstrated how to use the method in PAI. | [
1,
0,
0,
0,
0,
0
] | [
"Computer Science"
] |
Title: Non-singular spacetimes with a negative cosmological constant: IV. Stationary black hole solutions with matter fields,
Abstract: We use an elliptic system of equations with complex coefficients for a set of
complex-valued tensor fields as a tool to construct infinite-dimensional
families of non-singular stationary black holes, real-valued Lorentzian
solutions of the Einstein-Maxwell-dilaton-scalar
fields-Yang-Mills-Higgs-Chern-Simons-$f(R)$ equations with a negative
cosmological constant. The families include an infinite-dimensional family of
solutions with the usual AdS conformal structure at conformal infinity. | [
0,
0,
1,
0,
0,
0
] | [
"Physics"
] |
Title: Non-Hamiltonian isotopic Lagrangians on the one-point blow-up of CP^2,
Abstract: We show that two Hamiltonian isotopic Lagrangians in
(CP^2,\omega_\textup{FS}) induce two Lagrangian submanifolds in the one-point
blow-up (\widetilde{CP}^2,\widetilde{\omega}_\rho) that are not Hamiltonian
isotopic. Furthermore, we show that for any integer k>1 there are k Hamiltonian
isotopic Lagrangians in (CP^2,\omega_\textup{FS}) that induce k Lagrangian
submanifolds in the one-point blow-up such that no two of them are Hamiltonian
isotopic. | [
0,
0,
1,
0,
0,
0
] | [
"Mathematics",
"Physics"
] |
Title: Berezinskii-Kosterlitz-Thouless Type Scenario in Molecular Spin Liquid $A$Cr$_2$O$_4$,
Abstract: The spin relaxation in chromium spinel oxides $A$Cr$_{2}$O$_{4}$ ($A=$ Mg,
Zn, Cd) is investigated in the paramagnetic regime by electron spin resonance
(ESR). The temperature dependence of the ESR linewidth indicates an
unconventional spin-relaxation behavior, similar to spin-spin relaxation in the
two-dimensional (2D) chromium-oxide triangular lattice antiferromagnets. The
data can be described in terms of a generalized Berezinskii-Kosterlitz-Thouless
(BKT) type scenario for 2D systems with additional internal symmetries. Based
on the characteristic exponents obtained from the evaluation of the ESR
linewidth, short-range order with a hidden internal symmetry is suggested. | [
0,
1,
0,
0,
0,
0
] | [
"Physics"
] |
Title: Bayesian hierarchical weighting adjustment and survey inference,
Abstract: We combine Bayesian prediction and weighted inference as a unified approach
to survey inference. The general principles of Bayesian analysis imply that
models for survey outcomes should be conditional on all variables that affect
the probability of inclusion. We incorporate the weighting variables under the
framework of multilevel regression and poststratification, as a byproduct
generating model-based weights after smoothing. We investigate deep
interactions and introduce structured prior distributions for smoothing and
stability of estimates. The computation is done via Stan and implemented in the
open source R package "rstanarm" ready for public use. Simulation studies
illustrate that model-based prediction and weighting inference outperform
classical weighting. We apply the proposal to the New York Longitudinal Study
of Wellbeing. The new approach generates robust weights and increases
efficiency for finite population inference, especially for subsets of the
population. | [
0,
0,
0,
1,
0,
0
] | [
"Statistics",
"Mathematics"
] |
Title: Nonlocal Pertubations of Fractional Choquard Equation,
Abstract: We study the equation \begin{equation} (-\Delta)^{s}u+V(x)u=
(I_{\alpha}*|u|^{p})|u|^{p-2}u+\lambda(I_{\beta}*|u|^{q})|u|^{q-2}u \quad\mbox{
in } \R^{N}, \end{equation} where $I_\gamma(x)=|x|^{-\gamma}$ for any
$\gamma\in (0,N)$, $p, q >0$, $\alpha,\beta\in (0,N)$, $N\geq 3$ and $ \lambda
\in R$. First, the existence of a groundstate solutions using minimization
method on the associated Nehari manifold is obtained. Next, the existence of
least energy sign-changing solutions is investigated by considering the Nehari
nodal set. | [
0,
0,
1,
0,
0,
0
] | [
"Mathematics",
"Physics"
] |
Title: Clustering Patients with Tensor Decomposition,
Abstract: In this paper we present a method for the unsupervised clustering of
high-dimensional binary data, with a special focus on electronic healthcare
records. We present a robust and efficient heuristic to face this problem using
tensor decomposition. We present the reasons why this approach is preferable
for tasks such as clustering patient records, to more commonly used
distance-based methods. We run the algorithm on two datasets of healthcare
records, obtaining clinically meaningful results. | [
1,
0,
0,
1,
0,
0
] | [
"Computer Science",
"Statistics",
"Quantitative Biology"
] |
Title: Posterior distribution existence and error control in Banach spaces in the Bayesian approach to UQ in inverse problems,
Abstract: We generalize the results of \cite{Capistran2016} on expected Bayes factors
(BF) to control the numerical error in the posterior distribution to an
infinite dimensional setting when considering Banach functional spaces and now
in a prior setting. The main result is a bound on the absolute global error to
be tolerated by the Forward Map numerical solver, to keep the BF of the
numerical vs. the theoretical model near to 1, now in this more general
setting, possibly including a truncated, finite dimensional approximate prior
measure. In so doing we found a far more general setting to define and prove
existence of the infinite dimensional posterior distribution than that depicted
in, for example, \cite{Stuart2010}. Discretization consistency and rates of
convergence are also investigated in this general setting for the Bayesian
inverse problem. | [
0,
0,
1,
1,
0,
0
] | [
"Mathematics",
"Statistics"
] |
Title: High-$T_c$ mechanism through analysis of diverging effective mass for YaBa$_2$Cu$_3$O$_{6+x}$ and pairing symmetry in cuprate superconductors,
Abstract: In order to clarify the high-$T_c$ mechanism in inhomogeneous cuprate layer
superconductors, we deduce and find the correlation strength not revealed
before, contributing to the formation of the Cooper pair and the 2-D density of
state, and demonstrate the pairing symmetry in the superconductors still
controversial. To the open questions, the fitting and analysis of the diverging
effective mass with decreasing doping, extracted from the acquired
quantum-oscillation data in underdoped YBCOO$_{6+x}$ superconductors, can
provide solutions. Here, the results of the fitting using the extended
Brinkman-Rice(BR) picture reveal the nodal constant Fermi energy with the
maximum carrier density, a constant Coulomb correlation strength
$k_{BR}$=$U/U_c$>0.90, and a growing Fermi arc from the nodal Fermi point to
the isotropic Fermi surface with an increasing $x$. The growing of the Fermi
arc indicates that a superconducting gap develops with $x$ from the node to the
anti-node. The large $k_{BR}$ results from the $d$-wave MIT for the pseudogap
phase in lightly doped superconductors, which can be direct evidence for
high-$T_c$ superconductivity. The quantum critical point is regarded as the
nodal Fermi point satisfied with the BR picture. The experimentally-measured
mass diverging behavior is an average effect and the true effective mass is
constant. As an application of the nodal constant carrier density, to find a
superconducting node gap, the ARPES data and tunneling data are analyzed. The
superconducting node gap is a precursor of $s$-wave symmetry in underdoped
cuprates. The half-flux quantum, induced by the circulation of $d$-wave
supercurrent and observed by the phase sensitive Josephson-pi junction
experiments, is not shown due to anisotropic or asymmetric effect appearing in
superconductors with trapped flux. The absence of $d$-wave superconducting
pairing symmetry is also revealed. | [
0,
1,
0,
0,
0,
0
] | [
"Physics"
] |
Title: Look No Further: Adapting the Localization Sensory Window to the Temporal Characteristics of the Environment,
Abstract: Many localization algorithms use a spatiotemporal window of sensory
information in order to recognize spatial locations, and the length of this
window is often a sensitive parameter that must be tuned to the specifics of
the application. This letter presents a general method for environment-driven
variation of the length of the spatiotemporal window based on searching for the
most significant localization hypothesis, to use as much context as is
appropriate but not more. We evaluate this approach on benchmark datasets using
visual and Wi-Fi sensor modalities and a variety of sensory comparison
front-ends under in-order and out-of-order traversals of the environment. Our
results show that the system greatly reduces the maximum distance traveled
without localization compared to a fixed-length approach while achieving
competitive localization accuracy, and our proposed method achieves this
performance without deployment-time tuning. | [
1,
0,
0,
0,
0,
0
] | [
"Computer Science"
] |
Title: A two-dimensional data-driven model for traffic flow on highways,
Abstract: Based on experimental traffic data obtained from German and US highways, we
propose a novel two-dimensional first-order macroscopic traffic flow model. The
goal is to reproduce a detailed description of traffic dynamics for the real
road geometry. In our approach both the dynamic along the road and across the
lanes is continuous. The closure relations, being necessary to complete the
hydrodynamic equation, are obtained by regression on fundamental diagram data.
Comparison with prediction of one-dimensional models shows the improvement in
performance of the novel model. | [
0,
1,
0,
0,
0,
0
] | [
"Computer Science",
"Mathematics"
] |
Title: Cut Finite Element Methods for Elliptic Problems on Multipatch Parametric Surfaces,
Abstract: We develop a finite element method for the Laplace--Beltrami operator on a
surface described by a set of patchwise parametrizations. The patches provide a
partition of the surface and each patch is the image by a diffeomorphism of a
subdomain of the unit square which is bounded by a number of smooth trim
curves. A patchwise tensor product mesh is constructed by using a structured
mesh in the reference domain. Since the patches are trimmed we obtain cut
elements in the vicinity of the interfaces. We discretize the Laplace--Beltrami
operator using a cut finite element method that utilizes Nitsche's method to
enforce continuity at the interfaces and a consistent stabilization term to
handle the cut elements. Several quantities in the method are conveniently
computed in the reference domain where the mappings impose a Riemannian metric.
We derive a priori estimates in the energy and $L^2$ norm and also present
several numerical examples confirming our theoretical results. | [
0,
0,
1,
0,
0,
0
] | [
"Mathematics",
"Computer Science"
] |
Title: The p-adic Kummer-Leopoldt constant - Normalized p-adic regulator,
Abstract: The p-adic Kummer--Leopoldt constant kappa\_K of a number field K is
(assuming the Leopoldt conjecture) the least integer c such that for all n
\textgreater{}\textgreater{} 0, any global unit of K, which is locally a
p^(n+c)th power at the p-places, is necessarily the p^nth power of a global
unit of K. This constant has been computed by Assim \& Nguyen Quang Do using
Iwasawa's techniques,after intricate studies and calculations by many authors.
We give an elementary p-adic proof and an improvement of these results, then a
class field theory interpretation of kappa\_K. We give some applications
(including generalizations of Kummer's lemma on regular pth cyclotomic fields)
and a natural definition of the normalized p-adic regulator for any K and any
p$\ge$2.This is done without analytical computations, using only class field
theoryand especially the properties of the so-called p-torsion group T\_K of
Abelian p-ramification theory over K. | [
0,
0,
1,
0,
0,
0
] | [
"Mathematics"
] |
Title: Local-global principles in circle packings,
Abstract: We generalize work of Bourgain-Kontorovich and Zhang, proving an almost
local-to-global property for the curvatures of certain circle packings, to a
large class of Kleinian groups. Specifically, we associate in a natural way an
infinite family of integral packings of circles to any Kleinian group $\mathcal
A\leq\textrm{PSL}_2(K)$ satisfying certain conditions, where $K$ is an
imaginary quadratic field, and show that the curvatures of the circles in any
such packing satisfy an almost local-to-global principle. A key ingredient in
the proof of this is that $\mathcal A$ possesses a spectral gap property, which
we prove for any infinite-covolume, geometrically finite, Zariski dense
Kleinian group in $\textrm{PSL}_2(\mathcal{O}_K)$ containing a Zariski dense
subgroup of $\textrm{PSL}_2(\mathbb{Z})$. | [
0,
0,
1,
0,
0,
0
] | [
"Mathematics"
] |
Title: Asymptotics for Small Nonlinear Price Impact: a PDE Approach to the Multidimensional Case,
Abstract: We provide an asymptotic expansion of the value function of a
multidimensional utility maximization problem from consumption with small
non-linear price impact. In our model cross-impacts between assets are allowed.
In the limit for small price impact, we determine the asymptotic expansion of
the value function around its frictionless version. The leading order
correction is characterized by a nonlinear second order PDE related to an
ergodic control problem and a linear parabolic PDE. We illustrate our result on
a multivariate geometric Brownian motion price model. | [
0,
0,
0,
0,
0,
1
] | [
"Quantitative Finance",
"Mathematics"
] |
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