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Title: Fast kNN mode seeking clustering applied to active learning,
Abstract: A significantly faster algorithm is presented for the original kNN mode
seeking procedure. It has the advantages over the well-known mean shift
algorithm that it is feasible in high-dimensional vector spaces and results in
uniquely, well defined modes. Moreover, without any additional computational
effort it may yield a multi-scale hierarchy of clusterings. The time complexity
is just O(n^1.5). resulting computing times range from seconds for 10^4 objects
to minutes for 10^5 objects and to less than an hour for 10^6 objects. The
space complexity is just O(n). The procedure is well suited for finding large
sets of small clusters and is thereby a candidate to analyze thousands of
clusters in millions of objects.
The kNN mode seeking procedure can be used for active learning by assigning
the clusters to the class of the modal objects of the clusters. Its feasibility
is shown by some examples with up to 1.5 million handwritten digits. The
obtained classification results based on the clusterings are compared with
those obtained by the nearest neighbor rule and the support vector classifier
based on the same labeled objects for training. It can be concluded that using
the clustering structure for classification can be significantly better than
using the trained classifiers. A drawback of using the clustering for
classification, however, is that no classifier is obtained that may be used for
out-of-sample objects. | [
1,
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] |
Title: Towards a Flow- and Path-Sensitive Information Flow Analysis: Technical Report,
Abstract: This paper investigates a flow- and path-sensitive static information flow
analysis. Compared with security type systems with fixed labels, it has been
shown that flow-sensitive type systems accept more secure programs. We show
that an information flow analysis with fixed labels can be both flow- and
path-sensitive. The novel analysis has two major components: 1) a
general-purpose program transformation that removes false dataflow dependencies
in a program that confuse a fixed-label type system, and 2) a fixed-label type
system that allows security types to depend on path conditions. We formally
prove that the proposed analysis enforces a rigorous security property:
noninterference. Moreover, we show that the analysis is strictly more precise
than a classic flow-sensitive type system, and it allows sound control of
information flow in the presence of mutable variables without resorting to
run-time mechanisms. | [
1,
0,
0,
0,
0,
0
] |
Title: Low-temperature lattice effects in the spin-liquid candidate $κ$-(BEDT-TTF)$_2$Cu$_2$(CN)$_3$,
Abstract: The quasi-two-dimensional organic charge-transfer salt
$\kappa$-(BEDT-TTF)$_2$Cu$_2$(CN)$_3$ is one of the prime candidates for a
quantum spin-liquid due the strong spin frustration of its anisotropic
triangular lattice in combination with its proximity to the Mott transition.
Despite intensive investigations of the material's low-temperature properties,
several important questions remain to be answered. Particularly puzzling are
the 6\,K anomaly and the enigmatic effects observed in magnetic fields. Here we
report on low-temperature measurements of lattice effects which were shown to
be particularly strongly pronounced in this material (R. S. Manna \emph{et
al.}, Phys. Rev. Lett. \textbf{104}, 016403 (2010)). A special focus of our
study lies on sample-to-sample variations of these effects and their
implications on the interpretation of experimental data. By investigating
overall nine single crystals from two different batches, we can state that
there are considerable differences in the size of the second-order phase
transition anomaly around 6\,K, varying within a factor of 3. In addition, we
find field-induced anomalies giving rise to pronounced features in the sample
length for two out of these nine crystals for temperatures $T <$ 9 K. We
tentatively assign the latter effects to $B$-induced magnetic clusters
suspected to nucleate around crystal imperfections. These $B$-induced effects
are absent for the crystals where the 6\,K anomaly is most strongly pronounced.
The large lattice effects observed at 6\,K are consistent with proposed pairing
instabilities of fermionic excitations breaking the lattice symmetry. The
strong sample-to-sample variation in the size of the phase transition anomaly
suggests that the conversion of the fermions to bosons at the instability is
only partial and to some extent influenced by not yet identified
sample-specific parameters. | [
0,
1,
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] |
Title: Local approximation of non-holomorphic discs in almost complex manifolds,
Abstract: We provide a local approximation result of non-holomorphic discs with small
d-bar by pseudoholomorphic ones. As an application, we provide a certain gluing
construction. | [
0,
0,
1,
0,
0,
0
] |
Title: A Tutorial on Deep Learning for Music Information Retrieval,
Abstract: Following their success in Computer Vision and other areas, deep learning
techniques have recently become widely adopted in Music Information Retrieval
(MIR) research. However, the majority of works aim to adopt and assess methods
that have been shown to be effective in other domains, while there is still a
great need for more original research focusing on music primarily and utilising
musical knowledge and insight. The goal of this paper is to boost the interest
of beginners by providing a comprehensive tutorial and reducing the barriers to
entry into deep learning for MIR. We lay out the basic principles and review
prominent works in this hard to navigate the field. We then outline the network
structures that have been successful in MIR problems and facilitate the
selection of building blocks for the problems at hand. Finally, guidelines for
new tasks and some advanced topics in deep learning are discussed to stimulate
new research in this fascinating field. | [
1,
0,
0,
0,
0,
0
] |
Title: A Family of Metrics for Clustering Algorithms,
Abstract: We give the motivation for scoring clustering algorithms and a metric $M : A
\rightarrow \mathbb{N}$ from the set of clustering algorithms to the natural
numbers which we realize as \begin{equation} M(A) = \sum_i \alpha_i |f_i -
\beta_i|^{w_i} \end{equation} where $\alpha_i,\beta_i,w_i$ are parameters used
for scoring the feature $f_i$, which is computed empirically.. We give a method
by which one can score features such as stability, noise sensitivity, etc and
derive the necessary parameters. We conclude by giving a sample set of scores. | [
1,
0,
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] |
Title: Efficient Estimation of Generalization Error and Bias-Variance Components of Ensembles,
Abstract: For many applications, an ensemble of base classifiers is an effective
solution. The tuning of its parameters(number of classes, amount of data on
which each classifier is to be trained on, etc.) requires G, the generalization
error of a given ensemble. The efficient estimation of G is the focus of this
paper. The key idea is to approximate the variance of the class
scores/probabilities of the base classifiers over the randomness imposed by the
training subset by normal/beta distribution at each point x in the input
feature space. We estimate the parameters of the distribution using a small set
of randomly chosen base classifiers and use those parameters to give efficient
estimation schemes for G. We give empirical evidence for the quality of the
various estimators. We also demonstrate their usefulness in making design
choices such as the number of classifiers in the ensemble and the size of a
subset of data used for training that is needed to achieve a certain value of
generalization error. Our approach also has great potential for designing
distributed ensemble classifiers. | [
1,
0,
0,
1,
0,
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] |
Title: Generalized weighted Ostrowski and Ostrowski-Grüss type inequalities on time scales via a parameter function,
Abstract: We prove generalized weighted Ostrowski and Ostrowski--Grüss type
inequalities on time scales via a parameter function. In particular, our result
extends a result of Dragomir and Barnett. Furthermore, we apply our results to
the continuous, discrete, and quantum cases, to obtain some interesting new
inequalities. | [
0,
0,
1,
0,
0,
0
] |
Title: Universality in Chaos: Lyapunov Spectrum and Random Matrix Theory,
Abstract: We propose the existence of a new universality in classical chaotic systems
when the number of degrees of freedom is large: the statistical property of the
Lyapunov spectrum is described by Random Matrix Theory. We demonstrate it by
studying the finite-time Lyapunov exponents of the matrix model of a stringy
black hole and the mass deformed models. The massless limit, which has a dual
string theory interpretation, is special in that the universal behavior can be
seen already at t=0, while in other cases it sets in at late time. The same
pattern is demonstrated also in the product of random matrices. | [
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1,
0,
0,
0,
0
] |
Title: Fixed points of competitive threshold-linear networks,
Abstract: Threshold-linear networks (TLNs) are models of neural networks that consist
of simple, perceptron-like neurons and exhibit nonlinear dynamics that are
determined by the network's connectivity. The fixed points of a TLN, including
both stable and unstable equilibria, play a critical role in shaping its
emergent dynamics. In this work, we provide two novel characterizations for the
set of fixed points of a competitive TLN: the first is in terms of a simple
sign condition, while the second relies on the concept of domination. We apply
these results to a special family of TLNs, called combinatorial
threshold-linear networks (CTLNs), whose connectivity matrices are defined from
directed graphs. This leads us to prove a series of graph rules that enable one
to determine fixed points of a CTLN by analyzing the underlying graph.
Additionally, we study larger networks composed of smaller "building block"
subnetworks, and prove several theorems relating the fixed points of the full
network to those of its components. Our results provide the foundation for a
kind of "graphical calculus" to infer features of the dynamics from a network's
connectivity. | [
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0,
0,
0,
1,
0
] |
Title: Adversarial Variational Bayes Methods for Tweedie Compound Poisson Mixed Models,
Abstract: The Tweedie Compound Poisson-Gamma model is routinely used for modeling
non-negative continuous data with a discrete probability mass at zero. Mixed
models with random effects account for the covariance structure related to the
grouping hierarchy in the data. An important application of Tweedie mixed
models is pricing the insurance policies, e.g. car insurance. However, the
intractable likelihood function, the unknown variance function, and the
hierarchical structure of mixed effects have presented considerable challenges
for drawing inferences on Tweedie. In this study, we tackle the Bayesian
Tweedie mixed-effects models via variational inference approaches. In
particular, we empower the posterior approximation by implicit models trained
in an adversarial setting. To reduce the variance of gradients, we
reparameterize random effects, and integrate out one local latent variable of
Tweedie. We also employ a flexible hyper prior to ensure the richness of the
approximation. Our method is evaluated on both simulated and real-world data.
Results show that the proposed method has smaller estimation bias on the random
effects compared to traditional inference methods including MCMC; it also
achieves a state-of-the-art predictive performance, meanwhile offering a richer
estimation of the variance function. | [
0,
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] |
Title: Sampling of Temporal Networks: Methods and Biases,
Abstract: Temporal networks have been increasingly used to model a diversity of systems
that evolve in time; for example human contact structures over which dynamic
processes such as epidemics take place. A fundamental aspect of real-life
networks is that they are sampled within temporal and spatial frames.
Furthermore, one might wish to subsample networks to reduce their size for
better visualization or to perform computationally intensive simulations. The
sampling method may affect the network structure and thus caution is necessary
to generalize results based on samples. In this paper, we study four sampling
strategies applied to a variety of real-life temporal networks. We quantify the
biases generated by each sampling strategy on a number of relevant statistics
such as link activity, temporal paths and epidemic spread. We find that some
biases are common in a variety of networks and statistics, but one strategy,
uniform sampling of nodes, shows improved performance in most scenarios. Our
results help researchers to better design network data collection protocols and
to understand the limitations of sampled temporal network data. | [
1,
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0,
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0
] |
Title: Bridge Programs as an approach to improving diversity in physics,
Abstract: In most physical sciences, students from underrepresented minority (URM)
groups constitute a small percentage of earned degrees at the undergraduate and
graduate levels. Bridge programs can serve as an initiative to increase the
number of URM students that gain access to graduate school and earn advanced
degrees in physics. This talk discussed levels of representation in physical
sciences as well as some results and best practices of current bridge programs
in physics. The APS Bridge Program has enabled over 100 students to be placed
into Bridge or graduate programs in physics, while retaining 88% of those
placed. | [
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] |
Title: NEURAL: quantitative features for newborn EEG using Matlab,
Abstract: Background: For newborn infants in critical care, continuous monitoring of
brain function can help identify infants at-risk of brain injury. Quantitative
features allow a consistent and reproducible approach to EEG analysis, but only
when all implementation aspects are clearly defined.
Methods: We detail quantitative features frequently used in neonatal EEG
analysis and present a Matlab software package together with exact
implementation details for all features. The feature set includes stationary
features that capture amplitude and frequency characteristics and features of
inter-hemispheric connectivity. The software, a Neonatal Eeg featURe set in
mAtLab (NEURAL), is open source and freely available. The software also
includes a pre-processing stage with a basic artefact removal procedure.
Conclusions: NEURAL provides a common platform for quantitative analysis of
neonatal EEG. This will support reproducible research and enable comparisons
across independent studies. These features present summary measures of the EEG
that can also be used in automated methods to determine brain development and
health of the newborn in critical care. | [
0,
1,
0,
1,
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0
] |
Title: False Positive Reduction by Actively Mining Negative Samples for Pulmonary Nodule Detection in Chest Radiographs,
Abstract: Generating large quantities of quality labeled data in medical imaging is
very time consuming and expensive. The performance of supervised algorithms for
various tasks on imaging has improved drastically over the years, however the
availability of data to train these algorithms have become one of the main
bottlenecks for implementation. To address this, we propose a semi-supervised
learning method where pseudo-negative labels from unlabeled data are used to
further refine the performance of a pulmonary nodule detection network in chest
radiographs. After training with the proposed network, the false positive rate
was reduced to 0.1266 from 0.4864 while maintaining sensitivity at 0.89. | [
0,
0,
0,
1,
0,
0
] |
Title: On the status of the Born-Oppenheimer expansion in molecular systems theory,
Abstract: It is shown that the adiabatic Born-Oppenheimer expansion does not satisfy
the necessary condition for the applicability of perturbation theory. A simple
example of an exact solution of a problem that can not be obtained from the
Born-Oppenheimer expansion is given. A new version of perturbation theory for
molecular systems is proposed. | [
0,
1,
0,
0,
0,
0
] |
Title: Computing Tropical Prevarieties in Parallel,
Abstract: The computation of the tropical prevariety is the first step in the
application of polyhedral methods to compute positive dimensional solution sets
of polynomial systems. In particular, pretropisms are candidate leading
exponents for the power series developments of the solutions. The computation
of the power series may start as soon as one pretropism is available, so our
parallel computation of the tropical prevariety has an application in a
pipelined solver.
We present a parallel implementation of dynamic enumeration. Our first
distributed memory implementation with forked processes achieved good speedups,
but quite often resulted in large variations in the execution times of the
processes. The shared memory multithreaded version applies work stealing to
reduce the variability of the run time. Our implementation applies the thread
safe Parma Polyhedral Library (PPL), in exact arithmetic with the GNU
Multiprecision Arithmetic Library (GMP), aided by the fast memory allocations
of TCMalloc.
Our parallel implementation is capable of computing the tropical prevariety
of the cyclic 16-roots problem. We also report on computational experiments on
the $n$-body and $n$-vortex problems; our computational results compare
favorably with Gfan. | [
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] |
Title: 3k-4 theorem for ordered groups,
Abstract: Recently, G. A. Freiman, M. Herzog, P. Longobardi, M. Maj proved two
`structure theorems' for ordered groups \cite{FHLM}. We give elementary proof
of these two theorems. | [
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1,
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] |
Title: Cosmological searches for a non-cold dark matter component,
Abstract: We explore an extended cosmological scenario where the dark matter is an
admixture of cold and additional non-cold species. The mass and temperature of
the non-cold dark matter particles are extracted from a number of cosmological
measurements. Among others, we consider tomographic weak lensing data and Milky
Way dwarf satellite galaxy counts. We also study the potential of these
scenarios in alleviating the existing tensions between local measurements and
Cosmic Microwave Background (CMB) estimates of the $S_8$ parameter, with
$S_8=\sigma_8\sqrt{\Omega_m}$, and of the Hubble constant $H_0$. In principle,
a sub-dominant, non-cold dark matter particle with a mass $m_X\sim$~keV, could
achieve the goals above. However, the preferred ranges for its temperature and
its mass are different when extracted from weak lensing observations and from
Milky Way dwarf satellite galaxy counts, since these two measurements require
suppressions of the matter power spectrum at different scales. Therefore,
solving simultaneously the CMB-weak lensing tensions and the small scale crisis
in the standard cold dark matter picture via only one non-cold dark matter
component seems to be challenging. | [
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] |
Title: F-pure threshold and height of quasi-homogeneous polynomials,
Abstract: We consider a quasi-homogeneous polynomial $f \in \mathbb{Z}[x_0, \ldots,
x_N]$ of degree $w$ equal to the degree of $x_0 \cdots x_N$ and show that the
$F$-pure threshold of the reduction $f_p \in \mathbb{F}_p[x_0, \ldots, x_N]$ is
equal to the log canonical threshold if and only if the height of the
Artin-Mazur formal group associated to $H^{N-1}\left( X, {\mathbb{G}}_{m,X}
\right)$, where $X$ is the hypersurface given by $f$, is equal to 1. We also
prove that a similar result holds for Fermat hypersurfaces of degree $>N+1$.
Furthermore, we give examples of weighted Delsarte surfaces which show that
other values of the $F$-pure threshold of a quasi-homogeneous polynomial of
degree $w$ cannot be characterized by the height. | [
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1,
0,
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] |
Title: Bayesian Alignments of Warped Multi-Output Gaussian Processes,
Abstract: We propose a novel Bayesian approach to modelling nonlinear alignments of
time series based on latent shared information. We apply the method to the
real-world problem of finding common structure in the sensor data of wind
turbines introduced by the underlying latent and turbulent wind field. The
proposed model allows for both arbitrary alignments of the inputs and
non-parametric output warpings to transform the observations. This gives rise
to multiple deep Gaussian process models connected via latent generating
processes. We present an efficient variational approximation based on nested
variational compression and show how the model can be used to extract shared
information between dependent time series, recovering an interpretable
functional decomposition of the learning problem. We show results for an
artificial data set and real-world data of two wind turbines. | [
1,
0,
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1,
0,
0
] |
Title: Fast and unsupervised methods for multilingual cognate clustering,
Abstract: In this paper we explore the use of unsupervised methods for detecting
cognates in multilingual word lists. We use online EM to train sound segment
similarity weights for computing similarity between two words. We tested our
online systems on geographically spread sixteen different language groups of
the world and show that the Online PMI system (Pointwise Mutual Information)
outperforms a HMM based system and two linguistically motivated systems:
LexStat and ALINE. Our results suggest that a PMI system trained in an online
fashion can be used by historical linguists for fast and accurate
identification of cognates in not so well-studied language families. | [
1,
0,
0,
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0,
0
] |
Title: Classification of simple linearly compact Kantor triple systems over the complex numbers,
Abstract: Simple finite dimensional Kantor triple systems over the complex numbers are
classified in terms of Satake diagrams. We prove that every simple and linearly
compact Kantor triple system has finite dimension and give an explicit
presentation of all the classical and exceptional systems. | [
0,
0,
1,
0,
0,
0
] |
Title: Fermion condensation and super pivotal categories,
Abstract: We study fermionic topological phases using the technique of fermion
condensation. We give a prescription for performing fermion condensation in
bosonic topological phases which contain a fermion. Our approach to fermion
condensation can roughly be understood as coupling the parent bosonic
topological phase to a phase of physical fermions, and condensing pairs of
physical and emergent fermions. There are two distinct types of objects in
fermionic theories, which we call "m-type" and "q-type" particles. The
endomorphism algebras of q-type particles are complex Clifford algebras, and
they have no analogues in bosonic theories. We construct a fermionic
generalization of the tube category, which allows us to compute the
quasiparticle excitations in fermionic topological phases. We then prove a
series of results relating data in condensed theories to data in their parent
theories; for example, if $\mathcal{C}$ is a modular tensor category containing
a fermion, then the tube category of the condensed theory satisfies
$\textbf{Tube}(\mathcal{C}/\psi) \cong \mathcal{C} \times (\mathcal{C}/\psi)$.
We also study how modular transformations, fusion rules, and coherence
relations are modified in the fermionic setting, prove a fermionic version of
the Verlinde dimension formula, construct a commuting projector lattice
Hamiltonian for fermionic theories, and write down a fermionic version of the
Turaev-Viro-Barrett-Westbury state sum. A large portion of this work is devoted
to three detailed examples of performing fermion condensation to produce
fermionic topological phases: we condense fermions in the Ising theory, the
$SO(3)_6$ theory, and the $\frac{1}{2}\text{E}_6$ theory, and compute the
quasiparticle excitation spectrum in each of these examples. | [
0,
1,
1,
0,
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0
] |
Title: pyRecLab: A Software Library for Quick Prototyping of Recommender Systems,
Abstract: This paper introduces pyRecLab, a software library written in C++ with Python
bindings which allows to quickly train, test and develop recommender systems.
Although there are several software libraries for this purpose, only a few let
developers to get quickly started with the most traditional methods, permitting
them to try different parameters and approach several tasks without a
significant loss of performance. Among the few libraries that have all these
features, they are available in languages such as Java, Scala or C#, what is a
disadvantage for less experienced programmers more used to the popular Python
programming language. In this article we introduce details of pyRecLab, showing
as well performance analysis in terms of error metrics (MAE and RMSE) and
train/test time. We benchmark it against the popular Java-based library LibRec,
showing similar results. We expect programmers with little experience and
people interested in quickly prototyping recommender systems to be benefited
from pyRecLab. | [
1,
0,
0,
0,
0,
0
] |
Title: A unified theory of adaptive stochastic gradient descent as Bayesian filtering,
Abstract: We formulate stochastic gradient descent (SGD) as a Bayesian filtering
problem. Inference in the Bayesian setting naturally gives rise to BRMSprop and
BAdam: Bayesian variants of RMSprop and Adam. Remarkably, the Bayesian approach
recovers many features of state-of-the-art adaptive SGD methods, including
amoungst others root-mean-square normalization, Nesterov acceleration and
AdamW. As such, the Bayesian approach provides one explanation for the
empirical effectiveness of state-of-the-art adaptive SGD algorithms.
Empirically comparing BRMSprop and BAdam with naive RMSprop and Adam on MNIST,
we find that Bayesian methods have the potential to considerably reduce test
loss and classification error. | [
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] |
Title: Radiative effects during the assembly of direct collapse black holes,
Abstract: We perform a post-processing radiative feedback analysis on a 3D ab initio
cosmological simulation of an atomic cooling halo under the direct collapse
black hole (DCBH) scenario. We maintain the spatial resolution of the
simulation by incorporating native ray-tracing on unstructured mesh data,
including Monte Carlo Lyman-alpha (Ly{\alpha}) radiative transfer. DCBHs are
born in gas-rich, metal-poor environments with the possibility of Compton-thick
conditions, $N_H \gtrsim 10^{24} {\rm cm}^{-2}$. Therefore, the surrounding gas
is capable of experiencing the full impact of the bottled-up radiation
pressure. In particular, we find that multiple scattering of Ly{\alpha} photons
provides an important source of mechanical feedback after the gas in the
sub-parsec region becomes partially ionized, avoiding the bottleneck of
destruction via the two-photon emission mechanism. We provide detailed
discussion of the simulation environment, expansion of the ionization front,
emission and escape of Ly{\alpha} radiation, and Compton scattering. A sink
particle prescription allows us to extract approximate limits on the
post-formation evolution of the radiative feedback. Fully coupled Ly{\alpha}
radiation hydrodynamics will be crucial to consider in future DCBH simulations. | [
0,
1,
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0
] |
Title: Critical values in Bak-Sneppen type models,
Abstract: In the Bak-Sneppen model, the lowest fitness particle and its two nearest
neighbors are renewed at each temporal step with a uniform (0,1) fitness
distribution. The model presents a critical value that depends on the
interaction criteria (two nearest neighbors) and on the update procedure
(uniform). Here we calculate the critical value for models where one or both
properties are changed. We study models with non-uniform updates, models with
random neighbors and models with binary fitness and obtain exact results for
the average fitness and for $p_c$. | [
0,
1,
0,
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0
] |
Title: ASIC Implementation of Time-Domain Digital Backpropagation with Deep-Learned Chromatic Dispersion Filters,
Abstract: We consider time-domain digital backpropagation with chromatic dispersion
filters jointly optimized and quantized using machine-learning techniques.
Compared to the baseline implementations, we show improved BER performance and
>40% power dissipation reductions in 28-nm CMOS. | [
0,
0,
0,
1,
0,
0
] |
Title: A formalization of convex polyhedra based on the simplex method,
Abstract: We present a formalization of convex polyhedra in the proof assistant Coq.
The cornerstone of our work is a complete implementation of the simplex method,
together with the proof of its correctness and termination. This allows us to
define the basic predicates over polyhedra in an effective way (i.e., as
programs), and relate them with the corresponding usual logical counterparts.
To this end, we make an extensive use of the Boolean reflection methodology.
The benefit of this approach is that we can easily derive the proof of several
fundamental results on polyhedra, such as Farkas' Lemma, the duality theorem of
linear programming, and Minkowski's Theorem. | [
1,
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1,
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] |
Title: Weight Spectrum of Quasi-Perfect Binary Codes with Distance 4,
Abstract: We consider the weight spectrum of a class of quasi-perfect binary linear
codes with code distance 4. For example, extended Hamming code and Panchenko
code are the known members of this class. Also, it is known that in many cases
Panchenko code has the minimal number of weight 4 codewords. We give exact
recursive formulas for the weight spectrum of quasi-perfect codes and their
dual codes. As an example of application of the weight spectrum we derive a
lower estimate for the conditional probability of correction of erasure
patterns of high weights (equal to or greater than code distance). | [
1,
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0
] |
Title: Entanglement Entropy of Eigenstates of Quadratic Fermionic Hamiltonians,
Abstract: In a seminal paper [D. N. Page, Phys. Rev. Lett. 71, 1291 (1993)], Page
proved that the average entanglement entropy of subsystems of random pure
states is $S_{\rm ave}\simeq\ln{\cal D}_{\rm A} - (1/2) {\cal D}_{\rm
A}^2/{\cal D}$ for $1\ll{\cal D}_{\rm A}\leq\sqrt{\cal D}$, where ${\cal
D}_{\rm A}$ and ${\cal D}$ are the Hilbert space dimensions of the subsystem
and the system, respectively. Hence, typical pure states are (nearly) maximally
entangled. We develop tools to compute the average entanglement entropy
$\langle S\rangle$ of all eigenstates of quadratic fermionic Hamiltonians. In
particular, we derive exact bounds for the most general translationally
invariant models $\ln{\cal D}_{\rm A} - (\ln{\cal D}_{\rm A})^2/\ln{\cal D}
\leq \langle S \rangle \leq \ln{\cal D}_{\rm A} - [1/(2\ln2)] (\ln{\cal D}_{\rm
A})^2/\ln{\cal D}$. Consequently we prove that: (i) if the subsystem size is a
finite fraction of the system size then $\langle S\rangle<\ln{\cal D}_{\rm A}$
in the thermodynamic limit, i.e., the average over eigenstates of the
Hamiltonian departs from the result for typical pure states, and (ii) in the
limit in which the subsystem size is a vanishing fraction of the system size,
the average entanglement entropy is maximal, i.e., typical eigenstates of such
Hamiltonians exhibit eigenstate thermalization. | [
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] |
Title: The Compressed Model of Residual CNDS,
Abstract: Convolutional neural networks have achieved a great success in the recent
years. Although, the way to maximize the performance of the convolutional
neural networks still in the beginning. Furthermore, the optimization of the
size and the time that need to train the convolutional neural networks is very
far away from reaching the researcher's ambition. In this paper, we proposed a
new convolutional neural network that combined several techniques to boost the
optimization of the convolutional neural network in the aspects of speed and
size. As we used our previous model Residual-CNDS (ResCNDS), which solved the
problems of slower convergence, overfitting, and degradation, and compressed
it. The outcome model called Residual-Squeeze-CNDS (ResSquCNDS), which we
demonstrated on our sold technique to add residual learning and our model of
compressing the convolutional neural networks. Our model of compressing adapted
from the SQUEEZENET model, but our model is more generalizable, which can be
applied almost to any neural network model, and fully integrated into the
residual learning, which addresses the problem of the degradation very
successfully. Our proposed model trained on very large-scale MIT
Places365-Standard scene datasets, which backing our hypothesis that the new
compressed model inherited the best of the previous ResCNDS8 model, and almost
get the same accuracy in the validation Top-1 and Top-5 with 87.64% smaller in
size and 13.33% faster in the training time. | [
1,
0,
0,
0,
0,
0
] |
Title: Chow Rings of Mp_{0,2}(N,d) and Mbar_{0,2}(P^{N-1},d) and Gromov-Witten Invariants of Projective Hypersurfaces of Degree 1 and 2,
Abstract: In this paper, we prove formulas that represent two-pointed Gromov-Witten
invariant <O_{h^a}O_{h^b}>_{0,d} of projective hypersurfaces with d=1,2 in
terms of Chow ring of Mbar_{0,2}(P^{N-1},d), the moduli spaces of stable maps
from genus 0 stable curves to projective space P^{N-1}. Our formulas are based
on representation of the intersection number w(O_{h^a}O_{h^b})_{0,d}, which was
introduced by Jinzenji, in terms of Chow ring of Mp_{0,2}(N,d), the moduli
space of quasi maps from P^1 to P^{N-1} with two marked points. In order to
prove our formulas, we use the results on Chow ring of Mbar_{0,2}(P^{N-1},d),
that were derived by A. Mustata and M. Mustata. We also present explicit toric
data of Mp_{0,2}(N,d) and prove relations of Chow ring of Mp_{0,2}(N,d). | [
0,
0,
1,
0,
0,
0
] |
Title: Common Glass-Forming Spin-Liquid State in the Pyrochlore Magnets Dy$_2$Ti$_2$O$_7$ and Ho$_2$Ti$_2$O$_7$,
Abstract: Despite a well-ordered pyrochlore crystal structure and strong magnetic
interactions between the Dy$^{3+}$ or Ho$^{3+}$ ions, no long range magnetic
order has been detected in the pyrochlore titanates Ho$_2$Ti$_2$O$_7$ and
Dy$_2$Ti$_2$O$_7$. To explore the actual magnetic phase formed by cooling these
materials, we measure their magnetization dynamics using toroidal,
boundary-free magnetization transport techniques. We find that the dynamical
magnetic susceptibility of both compounds has the same distinctive
phenomenology, that is indistinguishable in form from that of the dielectric
permittivity of dipolar glass-forming liquids. Moreover, Ho$_2$Ti$_2$O$_7$ and
Dy$_2$Ti$_2$O$_7$ both exhibit microscopic magnetic relaxation times that
increase along the super-Arrhenius trajectories analogous to those observed in
glass-forming dipolar liquids. Thus, upon cooling below about 2K,
Dy$_2$Ti$_2$O$_7$ and Ho$_2$Ti$_2$O$_7$ both appear to enter the same magnetic
state exhibiting the characteristics of a glass-forming spin-liquid. | [
0,
1,
0,
0,
0,
0
] |
Title: CANA: A python package for quantifying control and canalization in Boolean Networks,
Abstract: Logical models offer a simple but powerful means to understand the complex
dynamics of biochemical regulation, without the need to estimate kinetic
parameters. However, even simple automata components can lead to collective
dynamics that are computationally intractable when aggregated into networks. In
previous work we demonstrated that automata network models of biochemical
regulation are highly canalizing, whereby many variable states and their
groupings are redundant (Marques-Pita and Rocha, 2013). The precise charting
and measurement of such canalization simplifies these models, making even very
large networks amenable to analysis. Moreover, canalization plays an important
role in the control, robustness, modularity and criticality of Boolean network
dynamics, especially those used to model biochemical regulation (Gates and
Rocha, 2016; Gates et al., 2016; Manicka, 2017). Here we describe a new
publicly-available Python package that provides the necessary tools to extract,
measure, and visualize canalizing redundancy present in Boolean network models.
It extracts the pathways most effective in controlling dynamics in these
models, including their effective graph and dynamics canalizing map, as well as
other tools to uncover minimum sets of control variables. | [
1,
0,
0,
0,
1,
0
] |
Title: Stable monoenergetic ion acceleration by a two color laser tweezer,
Abstract: In the past decades, the phenomenal progress in the development of
ultraintense lasers has opened up many exciting new frontiers in laser matter
physics, including laser plasma ion acceleration. Currently a major challenge
in this frontier is to find simple methods to stably produce monoenergetic ion
beams with sufficient charge for real applications. Here, we propose a novel
scheme using a two color laser tweezer to fulfill this goal. In this scheme,
two circularly polarized lasers with different wavelengths collide right on a
thin nano-foil target containing mixed ion species. The radiation pressure of
this laser pair acts like a tweezer to pinch and fully drag the electrons out,
forming a stable uniform accelerating field for the ions. Scaling laws and
three-dimensional particle-in-cell simulations confirm that high energy
(10-1000 MeV) high charge ($\sim 10^{10}$) proton beams with narrow energy
spread ($\sim4\%-20\%$) can be obtained by commercially available lasers. Such
a scheme may open up a new route for compact high quality ion sources for
various applications. | [
0,
1,
0,
0,
0,
0
] |
Title: The Frequent Network Neighborhood Mapping of the Human Hippocampus Shows Much More Frequent Neighbor Sets in Males Than in Females,
Abstract: In the study of the human connectome, the vertices and the edges of the
network of the human brain are analyzed: the vertices of the graphs are the
anatomically identified gray matter areas of the subjects; this set is exactly
the same for all the subjects. The edges of the graphs correspond to the axonal
fibers, connecting these areas. In the biological applications of graph theory,
it happens very rarely that scientists examine numerous large graphs on the
very same, labeled vertex set. Exactly this is the case in the study of the
connectomes. Because of the particularity of these sets of graphs, novel,
robust methods need to be developed for their analysis. Here we introduce the
new method of the Frequent Network Neighborhood Mapping for the connectome,
which serves as a robust identification of the neighborhoods of given vertices
of special interest in the graph. We apply the novel method for mapping the
neighborhoods of the human hippocampus and discover strong statistical
asymmetries between the connectomes of the sexes, computed from the Human
Connectome Project. We analyze 413 braingraphs, each with 463 nodes. We show
that the hippocampi of men have much more significantly frequent neighbor sets
than women; therefore, in a sense, the connections of the hippocampi are more
regularly distributed in men and more varied in women. Our results are in
contrast to the volumetric studies of the human hippocampus, where it was shown
that the relative volume of the hippocampus is the same in men and women. | [
0,
0,
0,
0,
1,
0
] |
Title: Recurrent Neural Networks as Weighted Language Recognizers,
Abstract: We investigate the computational complexity of various problems for simple
recurrent neural networks (RNNs) as formal models for recognizing weighted
languages. We focus on the single-layer, ReLU-activation, rational-weight RNNs
with softmax, which are commonly used in natural language processing
applications. We show that most problems for such RNNs are undecidable,
including consistency, equivalence, minimization, and the determination of the
highest-weighted string. However, for consistent RNNs the last problem becomes
decidable, although the solution length can surpass all computable bounds. If
additionally the string is limited to polynomial length, the problem becomes
NP-complete and APX-hard. In summary, this shows that approximations and
heuristic algorithms are necessary in practical applications of those RNNs. | [
1,
0,
0,
0,
0,
0
] |
Title: The OGLE Collection of Variable Stars. Over 450 000 Eclipsing and Ellipsoidal Binary Systems Toward the Galactic Bulge,
Abstract: We present a collection of 450 598 eclipsing and ellipsoidal binary systems
detected in the OGLE fields toward the Galactic bulge. The collection consists
of binary systems of all types: detached, semi-detached, and contact eclipsing
binaries, RS CVn stars, cataclysmic variables, HW Vir binaries, double periodic
variables, and even planetary transits. For all stars we provide the I- and
V-band time-series photometry obtained during the OGLE-II, OGLE-III, and
OGLE-IV surveys. We discuss methods used to identify binary systems in the OGLE
data and present several objects of particular interest. | [
0,
1,
0,
0,
0,
0
] |
Title: The discrete moment problem with nonconvex shape constraints,
Abstract: The discrete moment problem is a foundational problem in distribution-free
robust optimization, where the goal is to find a worst-case distribution that
satisfies a given set of moments. This paper studies the discrete moment
problems with additional "shape constraints" that guarantee the worst case
distribution is either log-concave or has an increasing failure rate. These
classes of shape constraints have not previously been studied in the
literature, in part due to their inherent nonconvexities. Nonetheless, these
classes of distributions are useful in practice. We characterize the structure
of optimal extreme point distributions by developing new results in reverse
convex optimization, a lesser-known tool previously employed in designing
global optimization algorithms. We are able to show, for example, that an
optimal extreme point solution to a moment problem with $m$ moments and
log-concave shape constraints is piecewise geometric with at most $m$ pieces.
Moreover, this structure allows us to design an exact algorithm for computing
optimal solutions in a low-dimensional space of parameters. Moreover, We
describe a computational approach to solving these low-dimensional problems,
including numerical results for a representative set of instances. | [
0,
0,
1,
1,
0,
0
] |
Title: Optimal Tuning of Two-Dimensional Keyboards,
Abstract: We give a new analysis of a tuning problem in music theory, pertaining
specifically to the approximation of harmonics on a two-dimensional keyboard.
We formulate the question as a linear programming problem on families of
constraints and provide exact solutions for many new keyboard dimensions. We
also show that an optimal tuning for harmonic approximation can be obtained for
any keyboard of given width, provided sufficiently many rows of octaves. | [
1,
0,
0,
0,
0,
0
] |
Title: Ultra Reliable Short Message Relaying with Wireless Power Transfer,
Abstract: We consider a dual-hop wireless network where an energy constrained relay
node first harvests energy through the received radio-frequency signal from the
source, and then uses the harvested energy to forward the source's information
to the destination node. The throughput and delay metrics are investigated for
a decode-and-forward relaying mechanism at finite blocklength regime and
delay-limited transmission mode. We consider ultra-reliable communication
scenarios under discussion for the next fifth-generation of wireless systems,
with error and latency constraints. The impact on these metrics of the
blocklength, information bits, and relay position is investigated. | [
1,
0,
0,
1,
0,
0
] |
Title: Chainspace: A Sharded Smart Contracts Platform,
Abstract: Chainspace is a decentralized infrastructure, known as a distributed ledger,
that supports user defined smart contracts and executes user-supplied
transactions on their objects. The correct execution of smart contract
transactions is verifiable by all. The system is scalable, by sharding state
and the execution of transactions, and using S-BAC, a distributed commit
protocol, to guarantee consistency. Chainspace is secure against subsets of
nodes trying to compromise its integrity or availability properties through
Byzantine Fault Tolerance (BFT), and extremely high-auditability,
non-repudiation and `blockchain' techniques. Even when BFT fails, auditing
mechanisms are in place to trace malicious participants. We present the design,
rationale, and details of Chainspace; we argue through evaluating an
implementation of the system about its scaling and other features; we
illustrate a number of privacy-friendly smart contracts for smart metering,
polling and banking and measure their performance. | [
1,
0,
0,
0,
0,
0
] |
Title: On Certain Properties of Convex Functions,
Abstract: This note deals with certain properties of convex functions. We provide
results on the convexity of the set of minima of these functions, the behaviour
of their subgradient set under restriction, and optimization of these functions
over an affine subspace. | [
0,
0,
1,
0,
0,
0
] |
Title: The detection of variable radio emission from the fast rotating magnetic hot B-star HR7355 and evidence for its X-ray aurorae,
Abstract: In this paper we investigate the multiwavelengths properties of the magnetic
early B-type star HR7355. We present its radio light curves at several
frequencies, taken with the Jansky Very Large Array, and X-ray spectra, taken
with the XMM X-ray telescope. Modeling of the radio light curves for the Stokes
I and V provides a quantitative analysis of the HR7355 magnetosphere. A
comparison between HR7355 and a similar analysis for the Ap star CUVir, allows
us to study how the different physical parameters of the two stars affect the
structure of the respective magnetospheres where the non-thermal electrons
originate. Our model includes a cold thermal plasma component that accumulates
at high magnetic latitudes that influences the radio regime, but does not give
rise to X-ray emission. Instead, the thermal X-ray emission arises from shocks
generated by wind stream collisions close to the magnetic equatorial plane. The
analysis of the X-ray spectrum of HR7355 also suggests the presence of a
non-thermal radiation. Comparison between the spectral index of the power-law
X-ray energy distribution with the non-thermal electron energy distribution
indicates that the non-thermal X-ray component could be the auroral signature
of the non-thermal electrons that impact the stellar surface, the same
non-thermal electrons that are responsible for the observed radio emission. On
the basis of our analysis, we suggest a novel model that simultaneously
explains the X-ray and the radio features of HR7355 and is likely relevant for
magnetospheres of other magnetic early type stars. | [
0,
1,
0,
0,
0,
0
] |
Title: Repulsive Fermi polarons with negative effective mass,
Abstract: Recent LENS experiment on a 3D Fermi gas has reported a negative effective
mass ($m^*<0$) of Fermi polarons in the strongly repulsive regime. There
naturally arise a question whether the negative $m^*$ is a precursor of the
instability towards phase separation (or itinerant ferromagnetism). In this
work, we make use of the exact solutions to study the ground state and
excitation properties of repulsive Fermi polarons in 1D, which can also exhibit
a negative $m^*$ in the super Tonks-Girardeau regime. By analyzing the total
spin, quasi-momentum distribution and pair correlations, we conclude that the
negative $m^*$ is irrelevant to the instability towards ferromagnetism or phase
separation, but rather an intrinsic feature of collective excitations for
fermions in the strongly repulsive regime. Surprisingly, for large and negative
$m^*$, such excitation is accompanied with a spin density modulation when the
majority fermions move closer to the impurity rather than being repelled far
away, contrary to the picture of phase separation. These results suggest an
alternative interpretation of negative $m^*$ as observed in recent LENS
experiment. | [
0,
1,
0,
0,
0,
0
] |
Title: Entropy Formula for Random $\mathbb{Z}^k$-actions,
Abstract: In this paper, entropies, including measure-theoretic entropy and topological
entropy, are considered for random $\mathbb{Z}^k$-actions which are generated
by random compositions of the generators of $\mathbb{Z}^k$-actions. Applying
Pesin's theory for commutative diffeomorphisms we obtain a measure-theoretic
entropy formula of $C^{2}$ random $\mathbb{Z}^k$-actions via the Lyapunov
spectra of the generators. Some formulas and bounds of topological entropy for
certain random $\mathbb{Z}^k$(or $\mathbb{Z}_+^k$ )-actions generated by more
general maps, such as Lipschitz maps, continuous maps on finite graphs and
$C^{1}$ expanding maps, are also obtained. Moreover, as an application, we give
a formula of Friedland's entropy for certain $C^{2}$ $\mathbb{Z}^k$-actions. | [
0,
0,
1,
0,
0,
0
] |
Title: The thermal phase curve offset on tidally- and non-tidally-locked exoplanets: A shallow water model,
Abstract: Using a shallow water model with time-dependent forcing we show that the peak
of an exoplanet thermal phase curve is, in general, offset from secondary
eclipse when the planet is rotating. That is, the planetary hot-spot is offset
from the point of maximal heating (the substellar point) and may lead or lag
the forcing; the extent and sign of the offset is a function of both the
rotation rate and orbital period of the planet. We also find that the system
reaches a steady-state in the reference frame of the moving forcing. The model
is an extension of the well studied Matsuno-Gill model into a full spherical
geometry and with a planetary-scale translating forcing representing the
insolation received on an exoplanet from a host star.
The speed of the gravity waves in the model is shown to be a key metric in
evaluating the phase curve offset. If the velocity of the substellar point
(relative to the planet's surface) exceeds that of the gravity waves then the
hotspot will lag the substellar point, as might be expected by consideration of
forced gravity wave dynamics. However, when the substellar point is moving
slower than the internal wavespeed of the system the hottest point can lead the
passage of the forcing. We provide an interpretation of this result by
consideration of the Rossby and Kelvin wave dynamics as well as, in the very
slowly rotating case, a one-dimensional model that yields an analytic solution.
Finally, we consider the inverse problem of constraining planetary rotation
rate from an observed phase curve. | [
0,
1,
0,
0,
0,
0
] |
Title: Extremely high magnetoresistance and conductivity in the type-II Weyl semimetals WP2 and MoP2,
Abstract: The peculiar band structure of semimetals exhibiting Dirac and Weyl crossings
can lead to spectacular electronic properties such as large mobilities
accompanied by extremely high magnetoresistance. In particular, two closely
neighbouring Weyl points of the same chirality are protected from annihilation
by structural distortions or defects, thereby significantly reducing the
scattering probability between them. Here we present the electronic properties
of the transition metal diphosphides, WP2 and MoP2, that are type-II Weyl
semimetals with robust Weyl points. We present transport and angle resolved
photoemission spectroscopy measurements, and first principles calculations. Our
single crystals of WP2 display an extremely low residual low-temperature
resistivity of 3 nohm-cm accompanied by an enormous and highly anisotropic
magnetoresistance above 200 million % at 63 T and 2.5 K. These properties are
likely a consequence of the novel Weyl fermions expressed in this compound. We
observe a large suppression of charge carrier backscattering in WP2 from
transport measurements. | [
0,
1,
0,
0,
0,
0
] |
Title: Crystal structure, site selectivity, and electronic structure of layered chalcogenide LaOBiPbS3,
Abstract: We have investigated the crystal structure of LaOBiPbS3 using neutron
diffraction and synchrotron X-ray diffraction. From structural refinements, we
found that the two metal sites, occupied by Bi and Pb, were differently
surrounded by the sulfur atoms. Calculated bond valence sum suggested that one
metal site was nearly trivalent and the other was nearly divalent. Neutron
diffraction also revealed site selectivity of Bi and Pb in the LaOBiPbS3
structure. These results suggested that the crystal structure of LaOBiPbS3 can
be regarded as alternate stacks of the rock-salt-type Pb-rich sulfide layers
and the LaOBiS2-type Bi-rich layers. From band calculations for an ideal
(LaOBiS2)(PbS) system, we found that the S bands of the PbS layer were
hybridized with the Bi bands of the BiS plane at around the Fermi energy, which
resulted in the electronic characteristics different from that of LaOBiS2.
Stacking the rock-salt type sulfide (chalcogenide) layers and the BiS2-based
layered structure could be a new strategy to exploration of new BiS2-based
layered compounds, exotic two-dimensional electronic states, or novel
functionality. | [
0,
1,
0,
0,
0,
0
] |
Title: On The Robustness of Epsilon Skew Extension for Burr III Distribution on Real Line,
Abstract: The Burr III distribution is used in a wide variety of fields of lifetime
data analysis, reliability theory, and financial literature, etc. It is defined
on the positive axis and has two shape parameters, say $c$ and $k$. These shape
parameters make the distribution quite flexible. They also control the tail
behavior of the distribution. In this study, we extent the Burr III
distribution to the real axis and also add a skewness parameter, say
$\varepsilon$, with epsilon-skew extension approach. When the parameters $c$
and $k$ have a relation such that $ck \approx 1 $ or $ck < 1 $, it is skewed
unimodal. Otherwise, it is skewed bimodal with the same level of peaks on the
negative and positive sides of real line. Thus, ESBIII distribution can capture
fitting the various data sets even when the number of parameters are three.
Location and scale form of this distribution are also given. Some
distributional properties of the new distribution are investigated. The maximum
likelihood (ML) estimation method for the parameters of ESBIII is considered.
The robustness properties of ML estimators are studied and also tail behaviour
of ESBIII distribution is examined. The applications on real data are
considered to illustrate the modeling capacity of this distribution in the
class of bimodal distributions. | [
0,
0,
1,
1,
0,
0
] |
Title: Topology and strong four fermion interactions in four dimensions,
Abstract: We study massless fermions interacting through a particular four fermion term
in four dimensions. Exact symmetries prevent the generation of bilinear fermion
mass terms. We determine the structure of the low energy effective action for
the auxiliary field needed to generate the four fermion term and find it has an
novel structure that admits topologically non-trivial defects with non-zero
Hopf invariant. We show that fermions propagating in such a background pick up
a mass without breaking symmetries. Furthermore pairs of such defects
experience a logarithmic interaction. We argue that a phase transition
separates a phase where these defects proliferate from a broken phase where
they are bound tightly. We conjecture that by tuning one additional operator
the broken phase can be eliminated with a single BKT-like phase transition
separating the massless from massive phases. | [
0,
1,
0,
0,
0,
0
] |
Title: An Evolutionary Game for User Access Mode Selection in Fog Radio Access Networks,
Abstract: The fog radio access network (F-RAN) is a promising paradigm for the fifth
generation wireless communication systems to provide high spectral efficiency
and energy efficiency. Characterizing users to select an appropriate
communication mode among fog access point (F-AP), and device-to-device (D2D) in
F-RANs is critical for performance optimization. Using evolutionary game
theory, we investigate the dynamics of user access mode selection in F-RANs.
Specifically, the competition among groups of potential users space is
formulated as a dynamic evolutionary game, and the evolutionary equilibrium is
the solution to this game. Stochastic geometry tool is used to derive the
proposals' payoff expressions for both F-AP and D2D users by taking into
account the different nodes locations, cache sizes as well as the delay cost.
The analytical results obtained from the game model are evaluated via
simulations, which show that the evolutionary game based access mode selection
algorithm can reach a much higher payoff than the max rate based algorithm. | [
1,
0,
0,
0,
0,
0
] |
Title: Latent Estimation of GDP, GDP per capita, and Population from Historic and Contemporary Sources,
Abstract: The concepts of Gross Domestic Product (GDP), GDP per capita, and population
are central to the study of political science and economics. However, a growing
literature suggests that existing measures of these concepts contain
considerable error or are based on overly simplistic modeling choices. We
address these problems by creating a dynamic, three-dimensional latent trait
model, which uses observed information about GDP, GDP per capita, and
population to estimate posterior prediction intervals for each of these
important concepts. By combining historical and contemporary sources of
information, we are able to extend the temporal and spatial coverage of
existing datasets for country-year units back to 1500 A.D through 2015 A.D.
and, because the model makes use of multiple indicators of the underlying
concepts, we are able to estimate the relative precision of the different
country-year estimates. Overall, our latent variable model offers a principled
method for incorporating information from different historic and contemporary
data sources. It can be expanded or refined as researchers discover new or
alternative sources of information about these concepts. | [
0,
0,
0,
1,
0,
0
] |
Title: Portfolio Optimization under Fast Mean-reverting and Rough Fractional Stochastic Environment,
Abstract: Fractional stochastic volatility models have been widely used to capture the
non-Markovian structure revealed from financial time series of realized
volatility. On the other hand, empirical studies have identified scales in
stock price volatility: both fast-time scale on the order of days and
slow-scale on the order of months. So, it is natural to study the portfolio
optimization problem under the effects of dependence behavior which we will
model by fractional Brownian motions with Hurst index $H$, and in the fast or
slow regimes characterized by small parameters $\eps$ or $\delta$. For the
slowly varying volatility with $H \in (0,1)$, it was shown that the first order
correction to the problem value contains two terms of order $\delta^H$, one
random component and one deterministic function of state processes, while for
the fast varying case with $H > \half$, the same form holds at order
$\eps^{1-H}$. This paper is dedicated to the remaining case of a fast-varying
rough environment ($H < \half$) which exhibits a different behavior. We show
that, in the expansion, only one deterministic term of order $\sqrt{\eps}$
appears in the first order correction. | [
0,
0,
0,
0,
0,
1
] |
Title: Triangle Generative Adversarial Networks,
Abstract: A Triangle Generative Adversarial Network ($\Delta$-GAN) is developed for
semi-supervised cross-domain joint distribution matching, where the training
data consists of samples from each domain, and supervision of domain
correspondence is provided by only a few paired samples. $\Delta$-GAN consists
of four neural networks, two generators and two discriminators. The generators
are designed to learn the two-way conditional distributions between the two
domains, while the discriminators implicitly define a ternary discriminative
function, which is trained to distinguish real data pairs and two kinds of fake
data pairs. The generators and discriminators are trained together using
adversarial learning. Under mild assumptions, in theory the joint distributions
characterized by the two generators concentrate to the data distribution. In
experiments, three different kinds of domain pairs are considered, image-label,
image-image and image-attribute pairs. Experiments on semi-supervised image
classification, image-to-image translation and attribute-based image generation
demonstrate the superiority of the proposed approach. | [
1,
0,
0,
1,
0,
0
] |
Title: Bose - Einstein condensation of triplons with a weakly broken U(1) symmetry,
Abstract: The low-temperature properties of certain quantum magnets can be described in
terms of a Bose-Einstein condensation (BEC) of magnetic quasiparticles
(triplons). Some mean-field approaches (MFA) to describe these systems, based
on the standard grand canonical ensemble, do not take the anomalous density
into account and leads to an internal inconsistency, as it has been shown by
Hohenberg and Martin, and may therefore produce unphysical results. Moreover,
an explicit breaking of the U(1) symmetry as observed, for example, in TlCuCl3
makes the application of MFA more complicated. In the present work, we develop
a self-consistent MFA approach, similar to the Hartree-Fock-Bogolyubov
approximation in the notion of representative statistical ensembles, including
the effect of a weakly broken U(1) symmetry. We apply our results on
experimental data of the quantum magnet TlCuCl3 and show that magnetization
curves and the energy dispersion can be well described within this
approximation assuming that the BEC scenario is still valid. We predict that
the shift of the critical temperature Tc due to a finite exchange anisotropy is
rather substantial even when the anisotropy parameter \gamma is small, e.g.,
\Delta T_c \approx 10%$ of Tc in H = 6T and for \gamma\approx 4 \mu eV. | [
0,
1,
0,
0,
0,
0
] |
Title: LPCNet: Improving Neural Speech Synthesis Through Linear Prediction,
Abstract: Neural speech synthesis models have recently demonstrated the ability to
synthesize high quality speech for text-to-speech and compression applications.
These new models often require powerful GPUs to achieve real-time operation, so
being able to reduce their complexity would open the way for many new
applications. We propose LPCNet, a WaveRNN variant that combines linear
prediction with recurrent neural networks to significantly improve the
efficiency of speech synthesis. We demonstrate that LPCNet can achieve
significantly higher quality than WaveRNN for the same network size and that
high quality LPCNet speech synthesis is achievable with a complexity under 3
GFLOPS. This makes it easier to deploy neural synthesis applications on
lower-power devices, such as embedded systems and mobile phones. | [
1,
0,
0,
0,
0,
0
] |
Title: On the interpretability and computational reliability of frequency-domain Granger causality,
Abstract: This is a comment to the paper 'A study of problems encountered in Granger
causality analysis from a neuroscience perspective'. We agree that
interpretation issues of Granger Causality in Neuroscience exist (partially due
to the historical unfortunate use of the name 'causality', as nicely described
in previous literature). On the other hand we think that the paper uses a
formulation of Granger causality which is outdated (albeit still used), and in
doing so it dismisses the measure based on a suboptimal use of it. Furthermore,
since data from simulated systems are used, the pitfalls that are found with
the used formulation are intended to be general, and not limited to
neuroscience. It would be a pity if this paper, even written in good faith,
became a wildcard against all possible applications of Granger Causality,
regardless of the hard work of colleagues aiming to seriously address the
methodological and interpretation pitfalls. In order to provide a balanced
view, we replicated their simulations used the updated State Space
implementation, proposed already some years ago, in which the pitfalls are
mitigated or directly solved. | [
0,
0,
1,
1,
0,
0
] |
Title: Artificial topological models based on a one-dimensional spin-dependent optical lattice,
Abstract: Topological matter is a popular topic in both condensed matter and cold atom
research. In the past decades, a variety of models have been identified with
fascinating topological features. Some, but not all, of the models can be found
in materials. As a fully controllable system, cold atoms trapped in optical
lattices provide an ideal platform to simulate and realize these topological
models. Here we present a proposal for synthesizing topological models in cold
atoms based on a one-dimensional (1D) spin-dependent optical lattice potential.
In our system, features such as staggered tunneling, staggered Zeeman field,
nearest-neighbor interaction, beyond-near-neighbor tunneling, etc. can be
readily realized. They underlie the emergence of various topological phases.
Our proposal can be realized with current technology and hence has potential
applications in quantum simulation of topological matter. | [
0,
1,
0,
0,
0,
0
] |
Title: Regular irreducible characters of a hyperspecial compact group,
Abstract: A parametrization of irreducible unitary representations associated with the
regular adjoint orbits of a hyperspecial compact subgroup of a reductive group
over a non-dyadic non-archimedean local filed is presented. The parametrization
is given by means of (a subset of) the character group of certain finite
abelian groups arising from the reductive group. Our method is based upon
Cliffod's theory and Weil representations over finite fields. It works under an
assumption of the triviality of certain Schur multipliers defined for an
algebraic group over a finite field. The assumption of the triviality has good
evidences in the case of general linear groups and highly probable in general. | [
0,
0,
1,
0,
0,
0
] |
Title: Active Exploration Using Gaussian Random Fields and Gaussian Process Implicit Surfaces,
Abstract: In this work we study the problem of exploring surfaces and building compact
3D representations of the environment surrounding a robot through active
perception. We propose an online probabilistic framework that merges visual and
tactile measurements using Gaussian Random Field and Gaussian Process Implicit
Surfaces. The system investigates incomplete point clouds in order to find a
small set of regions of interest which are then physically explored with a
robotic arm equipped with tactile sensors. We show experimental results
obtained using a PrimeSense camera, a Kinova Jaco2 robotic arm and Optoforce
sensors on different scenarios. We then demonstrate how to use the online
framework for object detection and terrain classification. | [
1,
0,
0,
0,
0,
0
] |
Title: Doing good vs. avoiding bad in prosocial choice: A refined test and extension of the morality preference hypothesis,
Abstract: Prosociality is fundamental to human social life, and, accordingly, much
research has attempted to explain human prosocial behavior. Capraro and Rand
(Judgment and Decision Making, 13, 99-111, 2018) recently provided experimental
evidence that prosociality in anonymous, one-shot interactions (such as
Prisoner's Dilemma and Dictator Game experiments) is not driven by
outcome-based social preferences - as classically assumed - but by a
generalized morality preference for "doing the right thing". Here we argue that
the key experiments reported in Capraro and Rand (2018) comprise prominent
methodological confounds and open questions that bear on influential
psychological theory. Specifically, their design confounds: (i) preferences for
efficiency with self-interest; and (ii) preferences for action with preferences
for morality. Furthermore, their design fails to dissociate the preference to
do "good" from the preference to avoid doing "bad". We thus designed and
conducted a preregistered, refined and extended test of the morality preference
hypothesis (N=801). Consistent with this hypothesis, our findings indicate that
prosociality in the anonymous, one-shot Dictator Game is driven by preferences
for doing the morally right thing. Inconsistent with influential psychological
theory, however, our results suggest the preference to do "good" was as potent
as the preference to avoid doing "bad" in this case. | [
0,
0,
0,
0,
1,
0
] |
Title: Why Bohr was (Mostly) Right,
Abstract: After a discussion of the Frauchiger-Renner argument that no 'single- world'
interpretation of quantum mechanics can be self-consistent, I propose a
'Bohrian' alternative to many-worlds or QBism as the rational option. | [
0,
1,
0,
0,
0,
0
] |
Title: Simultaneous Inference for High Dimensional Mean Vectors,
Abstract: Let $X_1, \ldots, X_n\in\mathbb{R}^p$ be i.i.d. random vectors. We aim to
perform simultaneous inference for the mean vector $\mathbb{E} (X_i)$ with
finite polynomial moments and an ultra high dimension. Our approach is based on
the truncated sample mean vector. A Gaussian approximation result is derived
for the latter under the very mild finite polynomial ($(2+\theta)$-th) moment
condition and the dimension $p$ can be allowed to grow exponentially with the
sample size $n$. Based on this result, we propose an innovative resampling
method to construct simultaneous confidence intervals for mean vectors. | [
0,
0,
1,
1,
0,
0
] |
Title: Responses in Large-Scale Structure,
Abstract: We introduce a rigorous definition of general power-spectrum responses as
resummed vertices with two hard and $n$ soft momenta in cosmological
perturbation theory. These responses measure the impact of long-wavelength
perturbations on the local small-scale power spectrum. The kinematic structure
of the responses (i.e., their angular dependence) can be decomposed
unambiguously through a "bias" expansion of the local power spectrum, with a
fixed number of physical response coefficients, which are only a function of
the hard wavenumber $k$. Further, the responses up to $n$-th order completely
describe the $(n+2)$-point function in the squeezed limit, i.e. with two hard
and $n$ soft modes, which one can use to derive the response coefficients. This
generalizes previous results, which relate the angle-averaged squeezed limit to
isotropic response coefficients. We derive the complete expression of first-
and second-order responses at leading order in perturbation theory, and present
extrapolations to nonlinear scales based on simulation measurements of the
isotropic response coefficients. As an application, we use these results to
predict the non-Gaussian part of the angle-averaged matter power spectrum
covariance ${\rm Cov}^{\rm NG}_{\ell = 0}(k_1,k_2)$, in the limit where one of
the modes, say $k_2$, is much smaller than the other. Without any free
parameters, our model results are in very good agreement with simulations for
$k_2 \lesssim 0.06\ h/{\rm Mpc}$, and for any $k_1 \gtrsim 2 k_2$. The
well-defined kinematic structure of the power spectrum response also permits a
quick evaluation of the angular dependence of the covariance matrix. While we
focus on the matter density field, the formalism presented here can be
generalized to generic tracers such as galaxies. | [
0,
1,
0,
0,
0,
0
] |
Title: Graph isomorphisms in quasi-polynomial time,
Abstract: Let us be given two graphs $\Gamma_1$, $\Gamma_2$ of $n$ vertices. Are they
isomorphic? If they are, the set of isomorphisms from $\Gamma_1$ to $\Gamma_2$
can be identified with a coset $H\cdot\pi$ inside the symmetric group on $n$
elements. How do we find $\pi$ and a set of generators of $H$?
The challenge of giving an always efficient algorithm answering these
questions remained open for a long time. Babai has recently shown how to solve
these problems -- and others linked to them -- in quasi-polynomial time, i.e.
in time $\exp\left(O(\log n)^{O(1)}\right)$. His strategy is based in part on
the algorithm by Luks (1980/82), who solved the case of graphs of bounded
degree. | [
0,
0,
1,
0,
0,
0
] |
Title: Hardware-Aware Machine Learning: Modeling and Optimization,
Abstract: Recent breakthroughs in Deep Learning (DL) applications have made DL models a
key component in almost every modern computing system. The increased popularity
of DL applications deployed on a wide-spectrum of platforms have resulted in a
plethora of design challenges related to the constraints introduced by the
hardware itself. What is the latency or energy cost for an inference made by a
Deep Neural Network (DNN)? Is it possible to predict this latency or energy
consumption before a model is trained? If yes, how can machine learners take
advantage of these models to design the hardware-optimal DNN for deployment?
From lengthening battery life of mobile devices to reducing the runtime
requirements of DL models executing in the cloud, the answers to these
questions have drawn significant attention.
One cannot optimize what isn't properly modeled. Therefore, it is important
to understand the hardware efficiency of DL models during serving for making an
inference, before even training the model. This key observation has motivated
the use of predictive models to capture the hardware performance or energy
efficiency of DL applications. Furthermore, DL practitioners are challenged
with the task of designing the DNN model, i.e., of tuning the hyper-parameters
of the DNN architecture, while optimizing for both accuracy of the DL model and
its hardware efficiency. Therefore, state-of-the-art methodologies have
proposed hardware-aware hyper-parameter optimization techniques. In this paper,
we provide a comprehensive assessment of state-of-the-art work and selected
results on the hardware-aware modeling and optimization for DL applications. We
also highlight several open questions that are poised to give rise to novel
hardware-aware designs in the next few years, as DL applications continue to
significantly impact associated hardware systems and platforms. | [
0,
0,
0,
1,
0,
0
] |
Title: Quadratic forms and Sobolev spaces of fractional order,
Abstract: We study quadratic functionals on $L^2(\mathbb{R}^d)$ that generate seminorms
in the fractional Sobolev space $H^s(\mathbb{R}^d)$ for $0 < s < 1$. The
functionals under consideration appear in the study of Markov jump processes
and, independently, in recent research on the Boltzmann equation. The
functional measures differentiability of a function $f$ in a similar way as the
seminorm of $H^s(\mathbb{R}^d)$. The major difference is that differences $f(y)
- f(x)$ are taken into account only if $y$ lies in some double cone with apex
at $x$ or vice versa. The configuration of double cones is allowed to be
inhomogeneous without any assumption on the spatial regularity. We prove that
the resulting seminorm is comparable to the standard one of
$H^s(\mathbb{R}^d)$. The proof follows from a similar result on discrete
quadratic forms in $\mathbb{Z}^d$, which is our second main result. We
establish a general scheme for discrete approximations of nonlocal quadratic
forms. Applications to Markov jump processes are discussed. | [
0,
0,
1,
0,
0,
0
] |
Title: General Latent Feature Modeling for Data Exploration Tasks,
Abstract: This paper introduces a general Bayesian non- parametric latent feature model
suitable to per- form automatic exploratory analysis of heterogeneous datasets,
where the attributes describing each object can be either discrete, continuous
or mixed variables. The proposed model presents several important properties.
First, it accounts for heterogeneous data while can be inferred in linear time
with respect to the number of objects and attributes. Second, its Bayesian
nonparametric nature allows us to automatically infer the model complexity from
the data, i.e., the number of features necessary to capture the latent
structure in the data. Third, the latent features in the model are
binary-valued variables, easing the interpretability of the obtained latent
features in data exploration tasks. | [
1,
0,
0,
1,
0,
0
] |
Title: The ALMA View of the OMC1 Explosion in Orion,
Abstract: Most massive stars form in dense clusters where gravitational interactions
with other stars may be common. The two nearest forming massive stars, the BN
object and Source I, located behind the Orion Nebula, were ejected with
velocities of $\sim$29 and $\sim$13 km s$^{-1}$ about 500 years ago by such
interactions. This event generated an explosion in the gas. New ALMA
observations show in unprecedented detail, a roughly spherically symmetric
distribution of over a hundred $^{12}$CO J=2$-$1 streamers with velocities
extending from V$_{LSR}$ =$-$150 to +145 km s$^{-1}$. The streamer radial
velocities increase (or decrease) linearly with projected distance from the
explosion center, forming a `Hubble Flow' confined to within 50 arcseconds of
the explosion center. They point toward the high proper-motion, shock-excited
H$_2$ and [Fe ii ] `fingertips' and lower-velocity CO in the H$_2$ wakes
comprising Orion's `fingers'. In some directions, the H$_2$ `fingers' extend
more than a factor of two farther from the ejection center than the CO
streamers. Such deviations from spherical symmetry may be caused by ejecta
running into dense gas or the dynamics of the N-body interaction that ejected
the stars and produced the explosion. This $\sim$10$^{48}$ erg event may have
been powered by the release of gravitational potential energy associated with
the formation of a compact binary or a protostellar merger. Orion may be the
prototype for a new class of stellar explosion responsible for luminous
infrared transients in nearby galaxies. | [
0,
1,
0,
0,
0,
0
] |
Title: Simultaneous diagonalisation of the covariance and complementary covariance matrices in quaternion widely linear signal processing,
Abstract: Recent developments in quaternion-valued widely linear processing have
established that the exploitation of complete second-order statistics requires
consideration of both the standard covariance and the three complementary
covariance matrices. Although such matrices have a tremendous amount of
structure and their decomposition is a powerful tool in a variety of
applications, the non-commutative nature of the quaternion product has been
prohibitive to the development of quaternion uncorrelating transforms. To this
end, we introduce novel techniques for a simultaneous decomposition of the
covariance and complementary covariance matrices in the quaternion domain,
whereby the quaternion version of the Takagi factorisation is explored to
diagonalise symmetric quaternion-valued matrices. This gives new insights into
the quaternion uncorrelating transform (QUT) and forms a basis for the proposed
quaternion approximate uncorrelating transform (QAUT) which simultaneously
diagonalises all four covariance matrices associated with improper quaternion
signals. The effectiveness of the proposed uncorrelating transforms is
validated by simulations on both synthetic and real-world quaternion-valued
signals. | [
1,
0,
0,
0,
0,
0
] |
Title: Experimental determination of the frequency and field dependence of Specific Loss Power in Magnetic Fluid Hyperthermia,
Abstract: Magnetic nanoparticles are promising systems for biomedical applications and
in particular for Magnetic Fluid Hyperthermia, a promising therapy that
utilizes the heat released by such systems to damage tumor cells. We present an
experimental study of the physical properties that influences the capability of
heat release, i.e. the Specific Loss Power, SLP, of three biocompatible
ferrofluid samples having a magnetic core of maghemite with different core
diameter d= 10.2, 14.6 and 19.7 nm. The SLP was measured as a function of
frequency f and intensity of the applied alternating magnetic field H, and it
turned out to depend on the core diameter, as expected. The results allowed us
to highlight experimentally that the physical mechanism responsible for the
heating is size-dependent and to establish, at applied constant frequency, the
phenomenological functional relationship SLP=cH^x, with 2<x<3 for all samples.
The x-value depends on sample size and field frequency/ intensity, here chosen
in the typical range of operating magnetic hyperthermia devices. For the
smallest sample, the effective relaxation time Teff=19.5 ns obtained from SLP
data is in agreement with the value estimated from magnetization data, thus
confirming the validity of the Linear Response Theory model for this system at
properly chosen field intensity and frequency. | [
0,
1,
0,
0,
0,
0
] |
Title: Performance of Optimal Data Shaping Codes,
Abstract: Data shaping is a coding technique that has been proposed to increase the
lifetime of flash memory devices. Several data shaping codes have been
described in recent work, including endurance codes and direct shaping codes
for structured data. In this paper, we study information-theoretic properties
of a general class of data shaping codes and prove a separation theorem stating
that optimal data shaping can be achieved by the concatenation of optimal
lossless compression with optimal endurance coding. We also determine the
expansion factor that minimizes the total wear cost. Finally, we analyze the
performance of direct shaping codes and establish a condition for their
optimality. | [
1,
0,
0,
0,
0,
0
] |
Title: Automatic Music Highlight Extraction using Convolutional Recurrent Attention Networks,
Abstract: Music highlights are valuable contents for music services. Most methods
focused on low-level signal features. We propose a method for extracting
highlights using high-level features from convolutional recurrent attention
networks (CRAN). CRAN utilizes convolution and recurrent layers for sequential
learning with an attention mechanism. The attention allows CRAN to capture
significant snippets for distinguishing between genres, thus being used as a
high-level feature. CRAN was evaluated on over 32,000 popular tracks in Korea
for two months. Experimental results show our method outperforms three baseline
methods through quantitative and qualitative evaluations. Also, we analyze the
effects of attention and sequence information on performance. | [
1,
0,
0,
1,
0,
0
] |
Title: On Oracle-Efficient PAC RL with Rich Observations,
Abstract: We study the computational tractability of PAC reinforcement learning with
rich observations. We present new provably sample-efficient algorithms for
environments with deterministic hidden state dynamics and stochastic rich
observations. These methods operate in an oracle model of computation --
accessing policy and value function classes exclusively through standard
optimization primitives -- and therefore represent computationally efficient
alternatives to prior algorithms that require enumeration. With stochastic
hidden state dynamics, we prove that the only known sample-efficient algorithm,
OLIVE, cannot be implemented in the oracle model. We also present several
examples that illustrate fundamental challenges of tractable PAC reinforcement
learning in such general settings. | [
0,
0,
0,
1,
0,
0
] |
Title: Distributed Estimation of Principal Eigenspaces,
Abstract: Principal component analysis (PCA) is fundamental to statistical machine
learning. It extracts latent principal factors that contribute to the most
variation of the data. When data are stored across multiple machines, however,
communication cost can prohibit the computation of PCA in a central location
and distributed algorithms for PCA are thus needed. This paper proposes and
studies a distributed PCA algorithm: each node machine computes the top $K$
eigenvectors and transmits them to the central server; the central server then
aggregates the information from all the node machines and conducts a PCA based
on the aggregated information. We investigate the bias and variance for the
resulting distributed estimator of the top $K$ eigenvectors. In particular, we
show that for distributions with symmetric innovation, the empirical top
eigenspaces are unbiased and hence the distributed PCA is "unbiased". We derive
the rate of convergence for distributed PCA estimators, which depends
explicitly on the effective rank of covariance, eigen-gap, and the number of
machines. We show that when the number of machines is not unreasonably large,
the distributed PCA performs as well as the whole sample PCA, even without full
access of whole data. The theoretical results are verified by an extensive
simulation study. We also extend our analysis to the heterogeneous case where
the population covariance matrices are different across local machines but
share similar top eigen-structures. | [
0,
0,
1,
1,
0,
0
] |
Title: Invariant algebraic surfaces of the FitzHugh-Nagumo system,
Abstract: In this paper, we characterize all the irreducible Darboux polynomials and
polynomial first integrals of FitzHugh-Nagumo (F-N) system. The method of the
weight homogeneous polynomials and the characteristic curves is widely used to
give a complete classification of Darboux polynomials of a system. However,
this method does not work for F-N system. Here by considering the Darboux
polynomials of an assistant system associated to F-N system, we classified the
invariant algebraic surfaces of F-N system. Our results show that there is no
invariant algebraic surface of F-N system in the biological parameters region. | [
0,
0,
1,
0,
0,
0
] |
Title: Toric actions and convexity in cosymplectic geometry,
Abstract: We prove a convexity theorem for Hamiltonian torus actions on compact
cosymplectic manifolds. We show that compact toric cosymplectic manifolds are
mapping tori of equivariant symplectomorphisms of toric symplectic manifolds. | [
0,
0,
1,
0,
0,
0
] |
Title: A Reassessment of Absolute Energies of the X-ray L Lines of Lanthanide Metals,
Abstract: We introduce a new technique for determining x-ray fluorescence line energies
and widths, and we present measurements made with this technique of 22 x-ray L
lines from lanthanide-series elements. The technique uses arrays of
transition-edge sensors, microcalorimeters with high energy-resolving power
that simultaneously observe both calibrated x-ray standards and the x-ray
emission lines under study. The uncertainty in absolute line energies is
generally less than 0.4 eV in the energy range of 4.5 keV to 7.5 keV. Of the
seventeen line energies of neodymium, samarium, and holmium, thirteen are found
to be consistent with the available x-ray reference data measured after 1990;
only two of the four lines for which reference data predate 1980, however, are
consistent with our results. Five lines of terbium are measured with
uncertainties that improve on those of existing data by factors of two or more.
These results eliminate a significant discrepancy between measured and
calculated x-ray line energies for the terbium Ll line (5.551 keV). The line
widths are also measured, with uncertainties of 0.6 eV or less on the
full-width at half-maximum in most cases. These measurements were made with an
array of approximately one hundred superconducting x- ray microcalorimeters,
each sensitive to an energy band from 1 keV to 8 keV. No energy-dispersive
spectrometer has previously been used for absolute-energy estimation at this
level of accuracy. Future spectrometers, with superior linearity and energy
resolution, will allow us to improve on these results and expand the
measurements to more elements and a wider range of line energies. | [
0,
1,
0,
0,
0,
0
] |
Title: Limitations of Source-Filter Coupling In Phonation,
Abstract: The coupling of vocal fold (source) and vocal tract (filter) is one of the
most critical factors in source-filter articulation theory. The traditional
linear source-filter theory has been challenged by current research which
clearly shows the impact of acoustic loading on the dynamic behavior of the
vocal fold vibration as well as the variations in the glottal flow pulses
shape. This paper outlines the underlying mechanism of source-filter
interactions; demonstrates the design and working principles of coupling for
the various existing vocal cord and vocal tract biomechanical models. For our
study, we have considered self-oscillating lumped-element models of the
acoustic source and computational models of the vocal tract as articulators. To
understand the limitations of source-filter interactions which are associated
with each of those models, we compare them concerning their mechanical design,
acoustic and physiological characteristics and aerodynamic simulation. | [
1,
0,
0,
0,
0,
0
] |
Title: Automatic Disambiguation of French Discourse Connectives,
Abstract: Discourse connectives (e.g. however, because) are terms that can explicitly
convey a discourse relation within a text. While discourse connectives have
been shown to be an effective clue to automatically identify discourse
relations, they are not always used to convey such relations, thus they should
first be disambiguated between discourse-usage non-discourse-usage. In this
paper, we investigate the applicability of features proposed for the
disambiguation of English discourse connectives for French. Our results with
the French Discourse Treebank (FDTB) show that syntactic and lexical features
developed for English texts are as effective for French and allow the
disambiguation of French discourse connectives with an accuracy of 94.2%. | [
1,
0,
0,
0,
0,
0
] |
Title: Polar codes with a stepped boundary,
Abstract: We consider explicit polar constructions of blocklength $n\rightarrow\infty$
for the two extreme cases of code rates $R\rightarrow1$ and $R\rightarrow0.$
For code rates $R\rightarrow1,$ we design codes with complexity order of $n\log
n$ in code construction, encoding, and decoding. These codes achieve the
vanishing output bit error rates on the binary symmetric channels with any
transition error probability $p\rightarrow 0$ and perform this task with a
substantially smaller redundancy $(1-R)n$ than do other known high-rate codes,
such as BCH codes or Reed-Muller (RM). We then extend our design to the
low-rate codes that achieve the vanishing output error rates with the same
complexity order of $n\log n$ and an asymptotically optimal code rate
$R\rightarrow0$ for the case of $p\rightarrow1/2.$ | [
1,
0,
0,
0,
0,
0
] |
Title: An efficient global optimization algorithm for maximizing the sum of two generalized Rayleigh quotients,
Abstract: Maximizing the sum of two generalized Rayleigh quotients (SRQ) can be
reformulated as a one-dimensional optimization problem, where the function
value evaluations are reduced to solving semi-definite programming (SDP)
subproblems. In this paper, we first use the dual SDP subproblem to construct
an explicit overestimation and then propose a branch-and-bound algorithm to
globally solve (SRQ). Numerical results demonstrate that it is even more
efficient than the recent SDP-based heuristic algorithm. | [
0,
0,
1,
0,
0,
0
] |
Title: Location Dependent Dirichlet Processes,
Abstract: Dirichlet processes (DP) are widely applied in Bayesian nonparametric
modeling. However, in their basic form they do not directly integrate
dependency information among data arising from space and time. In this paper,
we propose location dependent Dirichlet processes (LDDP) which incorporate
nonparametric Gaussian processes in the DP modeling framework to model such
dependencies. We develop the LDDP in the context of mixture modeling, and
develop a mean field variational inference algorithm for this mixture model.
The effectiveness of the proposed modeling framework is shown on an image
segmentation task. | [
1,
0,
0,
1,
0,
0
] |
Title: Shadows of characteristic cycles, Verma modules, and positivity of Chern-Schwartz-MacPherson classes of Schubert cells,
Abstract: Chern-Schwartz-MacPherson (CSM) classes generalize to singular and/or
noncompact varieties the classical total homology Chern class of the tangent
bundle of a smooth compact complex manifold. The theory of CSM classes has been
extended to the equivariant setting by Ohmoto. We prove that for an arbitrary
complex projective manifold $X$, the homogenized, torus equivariant CSM class
of a constructible function $\varphi$ is the restriction of the characteristic
cycle of $\varphi$ via the zero section of the cotangent bundle of $X$. This
extends to the equivariant setting results of Ginzburg and Sabbah. We
specialize $X$ to be a (generalized) flag manifold $G/B$. In this case CSM
classes are determined by a Demazure-Lusztig (DL) operator. We prove a `Hecke
orthogonality' of CSM classes, determined by the DL operator and its
Poincar{é} adjoint. We further use the theory of holonomic
$\mathcal{D}_X$-modules to show that the characteristic cycle of a Verma
module, restricted to the zero section, gives the CSM class of the
corresponding Schubert cell. Since the Verma characteristic cycles naturally
identify with the Maulik and Okounkov's stable envelopes, we establish an
equivalence between CSM classes and stable envelopes; this reproves results of
Rim{á}nyi and Varchenko. As an application, we obtain a Segre type formula
for CSM classes. In the non-equivariant case this formula is manifestly
positive, showing that the expansion in the Schubert basis of the CSM class of
a Schubert cell is effective. This proves a previous conjecture by Aluffi and
Mihalcea, and it extends previous positivity results by J. Huh in the Grassmann
manifold case. Finally, we generalize all of this to partial flag manifolds
$G/P$. | [
0,
0,
1,
0,
0,
0
] |
Title: Effects of tunnelling and asymmetry for system-bath models of electron transfer,
Abstract: We apply the newly derived nonadiabatic golden-rule instanton theory to
asymmetric models describing electron-transfer in solution. The models go
beyond the usual spin-boson description and have anharmonic free-energy
surfaces with different values for the reactant and product reorganization
energies. The instanton method gives an excellent description of the behaviour
of the rate constant with respect to asymmetry for the whole range studied. We
derive a general formula for an asymmetric version of Marcus theory based on
the classical limit of the instanton and find that this gives significant
corrections to the standard Marcus theory. A scheme is given to compute this
rate based only on equilibrium simulations. We also compare the rate constants
obtained by the instanton method with its classical limit to study the effect
of tunnelling and other quantum nuclear effects. These quantum effects can
increase the rate constant by orders of magnitude. | [
0,
1,
0,
0,
0,
0
] |
Title: Self-Modifying Morphology Experiments with DyRET: Dynamic Robot for Embodied Testing,
Abstract: If robots are to become ubiquitous, they will need to be able to adapt to
complex and dynamic environments. Robots that can adapt their bodies while
deployed might be flexible and robust enough to meet this challenge. Previous
work on dynamic robot morphology has focused on simulation, combining simple
modules, or switching between locomotion modes. Here, we present an alternative
approach: a self-reconfigurable morphology that allows a single four-legged
robot to actively adapt the length of its legs to different environments. We
report the design of our robot, as well as the results of a study that verifies
the performance impact of self-reconfiguration. This study compares three
different control and morphology pairs under different levels of servo supply
voltage in the lab. We also performed preliminary tests in different
uncontrolled outdoor environments to see if changes to the external environment
supports our findings in the lab. Our results show better performance with an
adaptable body, lending evidence to the value of self-reconfiguration for
quadruped robots. | [
1,
0,
0,
0,
0,
0
] |
Title: TumorNet: Lung Nodule Characterization Using Multi-View Convolutional Neural Network with Gaussian Process,
Abstract: Characterization of lung nodules as benign or malignant is one of the most
important tasks in lung cancer diagnosis, staging and treatment planning. While
the variation in the appearance of the nodules remains large, there is a need
for a fast and robust computer aided system. In this work, we propose an
end-to-end trainable multi-view deep Convolutional Neural Network (CNN) for
nodule characterization. First, we use median intensity projection to obtain a
2D patch corresponding to each dimension. The three images are then
concatenated to form a tensor, where the images serve as different channels of
the input image. In order to increase the number of training samples, we
perform data augmentation by scaling, rotating and adding noise to the input
image. The trained network is used to extract features from the input image
followed by a Gaussian Process (GP) regression to obtain the malignancy score.
We also empirically establish the significance of different high level nodule
attributes such as calcification, sphericity and others for malignancy
determination. These attributes are found to be complementary to the deep
multi-view CNN features and a significant improvement over other methods is
obtained. | [
1,
0,
0,
1,
0,
0
] |
Title: An apparatus architecture for femtosecond transmission electron microscopy,
Abstract: The motion of electrons in or near solids, liquids and gases can be tracked
by forcing their ejection with attosecond x-ray pulses, derived from
femtosecond lasers. The momentum of these emitted electrons carries the imprint
of the electronic state. Aberration corrected transmission electron microscopes
have observed individual atoms, and have sufficient energy sensitivity to
quantify atom bonding and electronic configurations. Recent developments in
ultrafast electron microscopy and diffraction indicate that spatial and
temporal information can be collected simultaneously. In the present work, we
push the capability of femtosecond transmission electron microscopy (fs-TEM)
towards that of the state of the art in ultrafast lasers and electron
microscopes. This is anticipated to facilitate unprecedented elucidation of
physical, chemical and biological structural dynamics on electronic time and
length scales. The fs-TEM numerically studied employs a nanotip source,
electrostatic acceleration to 70 keV, magnetic lens beam transport and
focusing, a condenser-objective around the sample and a terahertz temporal
compressor, including space charge effects during propagation. With electron
emission equivalent to a 20 fs laser pulse, we find a spatial resolution below
10 nm and a temporal resolution of below 10 fs will be feasible for pulses
comprised of on average 20 electrons. The influence of a transverse electric
field at the sample is modelled, indicating that a field of 1 V/$\mu$m can be
resolved. | [
0,
1,
0,
0,
0,
0
] |
Title: HourGlass: Predictable Time-based Cache Coherence Protocol for Dual-Critical Multi-Core Systems,
Abstract: We present a hardware mechanism called HourGlass to predictably share data in
a multi-core system where cores are explicitly designated as critical or
non-critical. HourGlass is a time-based cache coherence protocol for
dual-critical multi-core systems that ensures worst-case latency (WCL) bounds
for memory requests originating from critical cores. Although HourGlass does
not provide either WCL or bandwidth guarantees for memory requests from
non-critical cores, it promotes the use of timers to improve its bandwidth
utilization while still maintaining WCL bounds for critical cores. This
encourages a trade-off between the WCL bounds for critical cores, and the
improved memory bandwidth for non-critical cores via timer configurations. We
evaluate HourGlass using gem5, and with multithreaded benchmark suites
including SPLASH-2, and synthetic workloads. Our results show that the WCL for
critical cores with HourGlass is always within the analytical WCL bounds, and
provides a tighter WCL bound on critical cores compared to the state-of-the-art
real-time cache coherence protocol. Further, we show that HourGlass enables a
trade-off between provable WCL bounds for critical cores, and improved
bandwidth utilization for non-critical cores. The average-case performance of
HourGlass is comparable to the state-of-the-art real-time cache coherence
protocol, and suffers a slowdown of 1.43x and 1.46x compared to the
conventional MSI and MESI protocols. | [
1,
0,
0,
0,
0,
0
] |
Title: Frictional Effects on RNA Folding: Speed Limit and Kramers Turnover,
Abstract: We investigated frictional effects on the folding rates of a human telomerase
hairpin (hTR HP) and H-type pseudoknot from the Beet Western Yellow Virus (BWYV
PK) using simulations of the Three Interaction Site (TIS) model for RNA. The
heat capacity from TIS model simulations, calculated using temperature replica
exchange simulations, reproduces nearly quantitatively the available
experimental data for the hTR HP. The corresponding results for BWYV PK serve
as predictions. We calculated the folding rates ($k_\mathrm{F}$) from more than
100 folding trajectories for each value of the solvent viscosity ($\eta$) at a
fixed salt concentration of 200 mM. By using the theoretical estimate
($\propto$$\sqrt{N}$ where $N$ is the number of nucleotides) for folding free
energy barrier, $k_\mathrm{F}$ data for both the RNAs are quantitatively fit
using one-dimensional Kramers' theory with two parameters specifying the
curvatures in the unfolded basin and the barrier top. In the high-friction
regime ($\eta\gtrsim10^{-5}\,\textrm{Pa\ensuremath{\cdot}s}$), for both HP and
PK, $k_\mathrm{F}$s decrease as $1/\eta$ whereas in the low friction regime,
$k_\mathrm{F}$ values increase as $\eta$ increases, leading to a maximum
folding rate at a moderate viscosity
($\sim10^{-6}\,\textrm{Pa\ensuremath{\cdot}s}$), which is the Kramers turnover.
From the fits, we find that the speed limit to RNA folding at water viscosity
is between 1 and 4 $\mathrm{\mu s}$, which is in accord with our previous
theoretical prediction as well as results from several single molecule
experiments. Both the RNA constructs fold by parallel pathways. Surprisingly,
we find that the flux through the pathways could be altered by changing solvent
viscosity, a prediction that is more easily testable in RNA than in proteins. | [
0,
0,
0,
0,
1,
0
] |
Title: Adversarial examples for generative models,
Abstract: We explore methods of producing adversarial examples on deep generative
models such as the variational autoencoder (VAE) and the VAE-GAN. Deep learning
architectures are known to be vulnerable to adversarial examples, but previous
work has focused on the application of adversarial examples to classification
tasks. Deep generative models have recently become popular due to their ability
to model input data distributions and generate realistic examples from those
distributions. We present three classes of attacks on the VAE and VAE-GAN
architectures and demonstrate them against networks trained on MNIST, SVHN and
CelebA. Our first attack leverages classification-based adversaries by
attaching a classifier to the trained encoder of the target generative model,
which can then be used to indirectly manipulate the latent representation. Our
second attack directly uses the VAE loss function to generate a target
reconstruction image from the adversarial example. Our third attack moves
beyond relying on classification or the standard loss for the gradient and
directly optimizes against differences in source and target latent
representations. We also motivate why an attacker might be interested in
deploying such techniques against a target generative network. | [
0,
0,
0,
1,
0,
0
] |
Title: What Would a Graph Look Like in This Layout? A Machine Learning Approach to Large Graph Visualization,
Abstract: Using different methods for laying out a graph can lead to very different
visual appearances, with which the viewer perceives different information.
Selecting a "good" layout method is thus important for visualizing a graph. The
selection can be highly subjective and dependent on the given task. A common
approach to selecting a good layout is to use aesthetic criteria and visual
inspection. However, fully calculating various layouts and their associated
aesthetic metrics is computationally expensive. In this paper, we present a
machine learning approach to large graph visualization based on computing the
topological similarity of graphs using graph kernels. For a given graph, our
approach can show what the graph would look like in different layouts and
estimate their corresponding aesthetic metrics. An important contribution of
our work is the development of a new framework to design graph kernels. Our
experimental study shows that our estimation calculation is considerably faster
than computing the actual layouts and their aesthetic metrics. Also, our graph
kernels outperform the state-of-the-art ones in both time and accuracy. In
addition, we conducted a user study to demonstrate that the topological
similarity computed with our graph kernel matches perceptual similarity
assessed by human users. | [
1,
0,
0,
1,
0,
0
] |
Title: A sure independence screening procedure for ultra-high dimensional partially linear additive models,
Abstract: We introduce a two-step procedure, in the context of ultra-high dimensional
additive models, which aims to reduce the size of covariates vector and
distinguish linear and nonlinear effects among nonzero components. Our proposed
screening procedure, in the first step, is constructed based on the concept of
cumulative distribution function and conditional expectation of response in the
framework of marginal correlation. B-splines and empirical distribution
functions are used to estimate the two above measures. The sure property of
this procedure is also established. In the second step, a double penalization
based procedure is applied to identify nonzero and linear components,
simultaneously. The performance of the designed method is examined by several
test functions to show its capabilities against competitor methods when errors
distribution are varied. Simulation studies imply that the proposed screening
procedure can be applied to the ultra-high dimensional data and well detect the
in uential covariates. It is also demonstrate the superiority in comparison
with the existing methods. This method is also applied to identify most in
uential genes for overexpression of a G protein-coupled receptor in mice. | [
0,
0,
1,
1,
0,
0
] |
Title: Hilbert Transformation and $r\mathrm{Spin}(n)+\mathbb{R}^n$ Group,
Abstract: In this paper we study symmetry properties of the Hilbert transformation of
several real variables in the Clifford algebra setting. In order to describe
the symmetry properties we introduce the group $r\mathrm{Spin}(n)+\mathbb{R}^n,
r>0,$ which is essentially an extension of the ax+b group. The study concludes
that the Hilbert transformation has certain characteristic symmetry properties
in terms of $r\mathrm{Spin}(n)+\mathbb{R}^n.$ In the present paper, for $n=2$
and $3$ we obtain, explicitly, the induced spinor representations of the
$r\mathrm{Spin}(n)+\mathbb{R}^n$ group. Then we decompose the natural
representation of $r\mathrm{Spin}(n)+\mathbb{R}^n$ into the direct sum of some
two irreducible spinor representations, by which we characterize the Hilbert
transformation in $\mathbb{R}^3$ and $\mathbb{R}^2.$ Precisely, we show that a
nontrivial skew operator is the Hilbert transformation if and only if it is
invariant under the action of the $r\mathrm{Spin}(n)+\mathbb{R}^n, n=2,3,$
group. | [
0,
0,
1,
0,
0,
0
] |
Title: (G, μ)-displays and Rapoport-Zink spaces,
Abstract: Let (G, \mu) be a pair of a reductive group G over the p-adic integers and a
minuscule cocharacter {\mu} of G defined over an unramified extension. We
introduce and study "(G, \mu)-displays" which generalize Zink's Witt vector
displays. We use these to define certain Rapoport-Zink formal schemes purely
group theoretically, i.e. without p-divisible groups. | [
0,
0,
1,
0,
0,
0
] |
Title: Estimates of covering type and the number of vertices of minimal triangulations,
Abstract: The covering type of a space $X$ is defined as the minimal cardinality of a
good cover of a space that is homotopy equivalent to $X$. We derive estimates
for the covering type of $X$ in terms of other invariants of $X$, namely the
ranks of the homology groups, the multiplicative structure of the cohomology
ring and the Lusternik-Schnirelmann category of $X$. By relating the covering
type to the number of vertices of minimal triangulations of complexes and
combinatorial manifolds, we obtain, within a unified framework, several
estimates which are either new or extensions of results that have been
previously obtained by ad hoc combinatorial arguments. Moreover, our methods
give results that are valid for entire homotopy classes of spaces. | [
0,
0,
1,
0,
0,
0
] |
Title: DNA insertion mutations can be predicted by a periodic probability function,
Abstract: It is generally difficult to predict the positions of mutations in genomic
DNA at the nucleotide level. Retroviral DNA insertion is one mode of mutation,
resulting in host infections that are difficult to treat. This mutation process
involves the integration of retroviral DNA into the host-infected cellular
genomic DNA following the interaction between host DNA and a pre-integration
complex consisting of retroviral DNA and integrase. Here, we report that
retroviral insertion sites around a hotspot within the Zfp521 and N-myc genes
can be predicted by a periodic function that is deduced using the diffraction
lattice model. In conclusion, the mutagenesis process is described by a
biophysical model for DNA-DNA interactions. | [
0,
1,
0,
0,
0,
0
] |
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