HHousen/ParaSCI · Datasets at Hugging Face

sentence1 stringlengths 16 446	sentence2 stringlengths 14 436
the existing algorithms for solving the minimum sum-rate problem in for the finite linear source model start with an estimation of the minimum sum-rate .	the existing algorithms for solving the minimum sum-rate problem all start with an estimation of the minimum sumrate , eg , the ones in for non-asymptotic model .
motivated by this challenge , we designed an ec security architecture , the trust zone , in order to enhance and extend the 5g aaa approach to a cognitive solution .	motivated by this challenge , we designed an edge cloud security architecture , the trust zone , in order to enhance and extend the 5g aaa approach to a cognitive solution .
adjoint based error estimation is widely used for a host of numerical methods including finite elements , time integration , multi-scale simulations and inverse problems .	goal-oriented error estimation in general is based on duality techniques and has already been used for a variety of applications such as mesh refinement in finite element methods .
over the past few years , convolutional neural networks have become the leading approach in many vision-related tasks .	in recent years , deep neural networks have achieved great success in a variety of machine learning tasks .
for galaxies , the tpcf is a simple , fundamental statistic of the galaxy distribution .	for three of the four galaxies , a10 is a better match to the published bar lengths than either amax or amin .
moreover , their methods use an edgecentric program model , so it is difficult to implement them on current graph computing systems such as pregel .	however their methods are edge centric methods , which can not be easily applied to current vertex centric graph computing systems such as graphlab .
for exchange and correlation we applied the gradient corrected approach using the generalized gradient approximation functional following the approach suggested by perdew-burke-ernzerhof .	in these studies we applied the perdew-burke-ernzerhof generalized gradient approximation with tkatchenko-scheffler van der waals interactions as the exchange-correlation functional .
it would be interesting to explore this further .	clearly , it would be interesting to understand this phenomenon better .
as a classifier , we use an svm , implemented in sklearn under the name svc toolkit .	as classifier we use a traditional model , a support vector machine with linear kernel implemented in scikit-learn .
our value is consistent with the previous determinations by interferometry .	our mean ud diameter value is consistent with these two recent measurements .
we used the scikit-learn implementation , in with 1000 estimators .	we used the scikit-learn implementation with lof , osvm , if , knn , svm , rf and nn .
deep convolutional neural networks have achieved great success in various computer vision tasks such as image classification .	one of the commonly used architectures , namely convolutional neural network , has presented record breaking results in computer vision tasks such as object recognition and classification .
cosmic strings are topological defects which may have formed during a phase transition in the early universe .	cosmic strings are line-like topological defects that are likely to emerge through phase transitions with spontaneous symmetry breaking .
the exchange correlation between electrons was treated with generalized gradient approximation in the perdewburke-ernzerhof form .	the electron exchangecorrelation functional was treated using the generalized gradient approximation in the form proposed by perdew , burke , and ernzerhof .
a single defect in pbg environments can possess localized modes for frequencies inside the gap .	as it was stated earlier single defects in pbg environments can possess localized modes for frequencies inside the gap .
in this case , sequence detection can be performed using recurrent neural networks .	sequence detection can be performed using recurrent neural networks .
the attractors of iterated function systems , a basic tool is the box-covering method .	the attractors of iterated function systems , a basic tool is the box covering method , that can be applied to networks .
note that here the trispectrum terms may contribute an even larger correction on small scales .	note that on very small scales , the non-gaussian contribution from the trispectrum might be significant .
lattice-boltzmann simulations of liquid-gas and binary fluid mixtures .	lattice boltzmann simulation of nonideal fluids .
it is based on the bsp model and adopts the vertex-centric paradigm with explicit messages to support scalable big graph processing .	it adopts the bulksynchronous parallel model with explicit messages to let users implement graph algorithms in a vertex-centric way .
for our cnn , we use 300-dimensional word2vec word embeddings trained on googlenews dataset 3 , and 128 feature maps with filter width .	we use the 300-dimension word2vec embeddings pretrained on google news dataset with about 100 billion words .
deep convolutional neural networks have achieved great success in computer vision related tasks such as image classification , and so on .	in particular , convolutional neural networks have been very successful for image classification .
gauge theories on non-commutative spaces can arise in certain limits of string theory .	indeed , noncommutative field theories can be derived from string theory by the seiberg-witten limit .
deep convolutional neural networks have achieved great success in various computer vision tasks such as image classification .	convolutional neural networks provide state-of-the-art results for many machine learning challenges , such as image classification .
a classic algorithm called the probabilistic classifier chain is a state-of-the-art csmlc algorithm .	a classic algorithm called probabilistic classifier chain , an algorithm that extends from cc , is a state-of-the-art csmlc algorithm .
a method to prove that some families are fc , 2 .	a method to prove that some families are not fc , 3 .
since the diffraction-limited region of an approximate bessel beam extends over large propagation distances , multiple trapping of particles with a single beam becomes possible .	for example , simultaneous trapping of several particles over large axial distances is possible by using just one single bessel beam .
model-based test generation techniques can target specific scenarios or requirements more effectively .	model-based test generation techniques can target specific use cases or requirements far more efficiently and effectively .
an isomorphism is a morphism with a continuous inverse .	which satisfies φ is called a sequential isomorphism .
physical states also exist when solely scalar multiplets are concerned .	physical states also exit when solely scalar multiplets are concerned .
the air-suspended nanotubes are synthesized by alcohol chemical vapor deposition .	the nanotubes are synthesized by alcohol chemical vapor deposition from catalyst particles placed near the trenches .
we select the same set of 871 subjects used in , comprising 403 individuals with asd and 468 healthy controls acquired at 20 different sites .	we select the same set of 871 subjects used by abraham et al that met the imaging quality and phenotypic information criteria , comprising 403 individuals with asd and 468 healthy controls .
it has indeed been shown in zou that the lasso estimator does not have the oracle property even in the finite parameter setting .	as a consequence , zou shows that the adaptive lasso has the oracle property under some regularity conditions .
a possible solution to this sensitivity problem is the design of a special sensing chamber that controls humidity and delivers the gas to the sensors under predefined conditions .	a possible solution to this sensitivity problem is a design of a special sensing chamber that controls humidity and delivers the gas to the sensors under predefined conditions .
the flow-motion network was trained for 750k steps with the adam optimizer .	the network was trained using an adam optimizer for gradient descent .
in fact , the direct implementation is known to be slow for practical settings of σs .	in general , the direct implementation is slow for practical settings of σ s .
deep convolutional neural networks have made significant progress in classification problems , which have shown to generate good results when provided sufficient data .	convolutional neural networks , alexnet being some famous examples , have demonstrated impressive performance on object detection tasks and are considered particularly well suited for feature extraction and classification .
we use the metropolis algorithm to simulate two-dimensional ising system .	the monte carlo simulation that we perform employs the standard metropolis algorithm .
the conditions have recently proved important in constructing electromagnetic cloaking structures .	the db conditions have been shown to play a central role in electromagnetic cloaking problems .
in quantum mechanics h is the planck constant .	the firmest thing of all in quantum mechanics is the formalism itself .
the benefits of network coding for distributed storage were first formalized by the work of dimakis et al .	the benefits of network coding for distributed storage has been first formalized by the work of dimakis et al .
from the arguments given in this paper , one can also see that the pauli-villars regularization and dimensional regularization gives the same result on the transverse anomaly of the axial vector and vector current .	at this point we remark that instead of pauli-villars regularization , one can also employ other regularization schemes such as dimensional regularization to calculate the transverse anomalies .
in , izumi studied certain explicit examples of endomorphisms of cuntz algebras motivated by subfactor theory .	in particular , localized endomorphisms of the cuntz algebras were investigated in the framework of the jones index theory in .
the thick lines represent the phase boundaries .	the thick lines show the phase boundaries .
asymptotic distribution and variance calculations were recently developed for m-estimators in this regime , el karoui , 2013 , donoho and montanari , 2013 .	it was previously shown that the asymptotic distribution of m-estimators in this design is nontrivial , donoho and montanari , 2013 , el karoui , 2013 .
multi-task learning for neural networks in general and within nlp specifically has been widely studied .	multi-task learning has been extensively studied in the literature , with applications to a wide set of problems ranging from natural language processing .
this is because each nucleon in the projectile does not excite pion production independently .	this indicates each nucleon in the projectile excites pion production almost dependently .
generative adversarial network is a class of deep learning algorithms that is used for generative modeling .	generative adversarial networks are a class of artificial intelligence algorithms used in unsupervised machine learning , which are introduced by .
the asterisk denotes additional information in the text .	the asterisk denotes that this result is strictly valid only when also a time average is considered .
the lower plot indicates the tail of the distribution .	the high-k tail of the distribution is shown in the lower plot .
note that if an energy estimate with bounding properties is used , then a similar bounding of the error in the quantity of interest can be obtained .	note that if we use an energy estimate with bounding properties , then the error estimate for the quantity of interest is bounded .
the belle detector is a large-solid-angle spectrometer based on a 1 5 t superconducting solenoid magnet .	the belle detector is a large-solid-angle magnetic spectrometer that consists of a three-layer silicon vertex detector .
the ultracold bose gas in optical lattices is well described by the bose-hubbard model .	in particular , bosons in optical lattices are near ideal realizations of the bose-hubbard model .
the generic architectures of the homogeneously encoded and heterogeneously encoded asynchronous rcas are given in and the reader is referred to the same for details .	the circuit architectures of the homogeneously and heterogeneously encoded asynchronous adders are given in , and the interested reader is referred to the same for details .
deep neural networks have shown improvement in state-of-the-art in different tasks , such as image classification .	deep neural networks have been adopted to improve the performance of state-of-the-arts on a wide variety of tasks in computer vision , including image classification .
specifically , convolutional neural networks have proved its effectiveness in a wide range of applications such as object recognition .	deep neural networks have significantly improved the state of the art on many supervised tasks .
summation formulas for the penalization terms .	discrete duality formulas for the convection terms .
cluster algebras form a large , axiomatically defined class of algebras , introduced by fomin and zelevinsky .	cluster algebras were introduced by fomin and zelevinsky in the series of papers .
our approach relies on the theory of graph signal processing .	we do so by building on the theory of graph signal processing .
more recently , graph attention networks have been introduced as an effective alternative for graph data modeling .	recently , graph convolutional networks have been widely studied for graph representation and learning .
although string theory is a strong candidate of it , the dynamics of the fermion states in string theories has not yet been extensively studied .	more importantly , string theory is a perfectly quantum mechanical theory which does include gravity .
such an asymmetry is the remnant of the partonic asymmetry .	this asymmetry is the origin of the finite real part of the soft mode .
the generalized gradient approximation according to perdewburke-ernzerhof was employed for both the generation of the pseudopotentials and the exchange-correlation functional .	the generalized gradient approximation of perdew-burkeernzerhof 30 type was employed for the exchange-correlation energy .
convolutional neural networks have achieved remarkable successes for various tasks , such as object recognition and so on .	convolutional neural networks have recently provided state of the art results for several recognition tasks including object recognition .
the encoder in the epva method is initialized with the vgg network pretrained on imagenet .	the network is initialized with the weights from the pretrained resnet-101 model on imagenet .
these networks have shown impressive results on computer vision tasks such as image labeling and object detection .	these visual representations have been shown to be effective on a wide range of computer vision tasks .
deep neural networks have achieved state-of-the-art performance on tasks such as image recognition in the last few years .	with the recent advances in deep convolutional neural networks , numerous image generation methods have achieved the state-of-the-art results .
the result of the ks-test is the probability of null-hypothesis that two distributions of the indicator are generated from the same population .	the result of the ks-test is the probability of the null-hypothesis that two distributions of the indicator are generated from the same population .
convolutional neural networks have improved the performance of image classification significantly .	object recognition has made significant progress with convolutional neural networks .
it is natural to conjecture that this is the unique non-zero irreducible object of this category .	a natural conjecture to make is the following .
hu et al propose the squeezeand-excitation block that adaptively recalibrates channelwise feature responses by explicitly modelling interdependencies between channels .	recently , hu et al proposes the squeeze-andexcitation block , which adaptively recalibrates channelwise feature responses by explicitly modelling interdependencies between channels .
the saturation below 1gev is the result of the fixed age of the cr particles , which is caused by the dynamical arms .	this contribution is negative , and is called normal saturation .
for c sb , we can use the floyd-warshall algorithm to compute all-pairs shortest paths in a graph .	the floyd-warshall algorithm is usually used to calculate all the pairs-shortest-paths in 1 g and 2 g .
set a contact lie group is a dimension n is called a legendrian submanifold of g .	this submanifold is the only tangentially degenerate submanifold without singularities in p n .
a different proof , based on the jones polynomial , follows from .	one proof which uses directly this relation to the jones polynomial is given in .
see labourie for definitions and more detailed discussions of anosov representations .	in this section , we recall the definition and basic properties of anosov representations , see labourie for further details .
phillips , university of arizona press , tuscon , pp .	gehrels , university of arizona press , tucson , pp .
there is growing evidence that all the known perturbative ten dimensional superstring theories are limits of an eleven dimensional theory called m theory .	the dualities between various superstring theories and m theory provide strong constraints on their effective actions .
since the higgs field is a component of the four-dimensional gluon field , no linear divergence of the higgs self-energy can occur due to the slavnov-taylor identities of the four-dimensional theory .	the higgs field is the responsible for triggering this ewsb mechanism .
we show that taking into account adiabatic expansion losses it is possible to describe the spectral evolution during the decay phase of individual pulses in long grbs .	finally , we argue that the observed spectral behavior of long pulses , during the grb decay phase of the light curve , can be described taking into account the energy loss for adiabatic expansion .
if there is no overshoot , which happens in particular in models with continuous asset prices , then the growth-optimal portfolio is indeed optimal .	if the objective is somewhat altered into minimizing expected market time , as we shall define below , then the growth-optimal portfolio is indeed optimal .
the ellipses denote the terms that are suppressed by positive powers of b .	where ellipses denote higher-twist contributions , ψ is a quark field and m is the nucleon mass .
various combinations of optical oscillations and tunneling ( bo , do and zt ) are formed as demonstrated on the phase diagram .	various superpositions of optical oscillations and zt are shown on the phase diagram .
kirkpatrick et al proposes elastic weight consolidation whose objective is to minimize the change of weights that are important to previous tasks through the use of a quadratic constraint .	recently , kirkpatrick et al proposed elastic weight consolidation , a quadratic penalty on the difference between the parameters for the new and the old task .
goodfellow et al claim that , in the case of neural networks , there is an excess of linearity in the behaviour of the networks .	goodfellow et al validate that practical attack in deep neural networks is possible because these models are locally linear .
we simulate the performance of our diva profiling mechanism using a modified version of ramulator .	we evaluate voltron using ramulator , integrated with a multicore performance simulator .
the aforementioned narrowband systems use measurements of the radio to extract information about people in the surrounding environment and therefore , such networks are referred to as rf sensor networks .	in general , these systems utilize received signal strength measurements of the radio for gaining situational awareness of the surrounding environment and therefore , they are commonly referred to as rf sensor networks .
ei buchbinder , il buchbinder , sm kuzenko , phys .	il buchbinder , ei buchbinder , sm kuzenko , ba ovrut , phys .
cluster algebras have been introduced by fomin and zelevinsky in in the context of total positivity and canonical bases in lie theory .	cluster algebras were introduced by fomin and zelevinsky in in order to study total positivity and canonical bases in semisimple groups .
our proposed method is implemented based on the deep learning library pytorch .	we have implemented our method by using pytorch , which is one of the most famous machine learning library .
since only the weak convergence was obtained in , no convergence rate was provided .	however , since only the weak convergence was obtained in , no convergence rate was provided there .
recently , deep convolutional neural networks have attracted much research attention in visual recognition , largely due to their excellent performance .	deep convolutional neural networks have been successful in many computer vision tasks including image classification .
wang et al propose a recurrent fully convolutional network for saliency detection that includes priors to correct initial saliency detection errors .	wang et al generated saliency prior maps using low-level cues and further exploited it to guide the prediction of saliency recurrently .
we implement the proposed model using pytorch on a single nvidia p40 gpu .	we implement the deep affinity network using the pytorch framework .
like many previous researches , this paper compares the performance of its proposed method with other individual clustering methods and cluster ensemble methods by using standard data sets and their real classes .	like many pervious researches , this paper compares the performance of its proposed method with other individual clustering methods and cluster ensemble methods by using standard datasets and their real classes .
to minimize the error of linear queries under differential privacy requirements , several methods try to build a synopsis of the original database , such as fourier transformations .	to minimize the error of linear queries under differential privacy requirements , several methods try to build a synopsis of the original database , such as fourier transformations and hierarchical trees .
starting with the work of li and haldane , the behavior of entanglement spectrum of two-dimensional systems has been extensively studied .	starting with the work of li and haldane , the behavior of the entanglement spectrum of twodimensional systems has been extensively studied .
silicon is the most widely used semiconductor in microelectronics .	silicon is a promising candidate for constructing a cavity-phoniton system .
recurrent neural networks have been gaining popularity in the machine learning community due to their impressive performance on tasks such as machine translation .	deep neural networks have become an extremely popular learning technique , with significant deployment in a wide variety of practical domains such as image classification .
socher et al , 2012 , uses a recursive neural network in relation extraction , and further use lstm .	miwa et al , used long short term memory based rnns for relation classification .

the existing algorithms for solving the minimum sum-rate problem in for the finite linear source model start with an estimation of the minimum sum-rate .

the existing algorithms for solving the minimum sum-rate problem all start with an estimation of the minimum sumrate , eg , the ones in for non-asymptotic model .

motivated by this challenge , we designed an ec security architecture , the trust zone , in order to enhance and extend the 5g aaa approach to a cognitive solution .

motivated by this challenge , we designed an edge cloud security architecture , the trust zone , in order to enhance and extend the 5g aaa approach to a cognitive solution .

adjoint based error estimation is widely used for a host of numerical methods including finite elements , time integration , multi-scale simulations and inverse problems .

goal-oriented error estimation in general is based on duality techniques and has already been used for a variety of applications such as mesh refinement in finite element methods .

over the past few years , convolutional neural networks have become the leading approach in many vision-related tasks .

in recent years , deep neural networks have achieved great success in a variety of machine learning tasks .

for galaxies , the tpcf is a simple , fundamental statistic of the galaxy distribution .

for three of the four galaxies , a10 is a better match to the published bar lengths than either amax or amin .

moreover , their methods use an edgecentric program model , so it is difficult to implement them on current graph computing systems such as pregel .

however their methods are edge centric methods , which can not be easily applied to current vertex centric graph computing systems such as graphlab .

for exchange and correlation we applied the gradient corrected approach using the generalized gradient approximation functional following the approach suggested by perdew-burke-ernzerhof .

in these studies we applied the perdew-burke-ernzerhof generalized gradient approximation with tkatchenko-scheffler van der waals interactions as the exchange-correlation functional .

it would be interesting to explore this further .

clearly , it would be interesting to understand this phenomenon better .

as a classifier , we use an svm , implemented in sklearn under the name svc toolkit .

as classifier we use a traditional model , a support vector machine with linear kernel implemented in scikit-learn .

our value is consistent with the previous determinations by interferometry .

our mean ud diameter value is consistent with these two recent measurements .

we used the scikit-learn implementation , in with 1000 estimators .

we used the scikit-learn implementation with lof , osvm , if , knn , svm , rf and nn .

deep convolutional neural networks have achieved great success in various computer vision tasks such as image classification .

one of the commonly used architectures , namely convolutional neural network , has presented record breaking results in computer vision tasks such as object recognition and classification .

cosmic strings are topological defects which may have formed during a phase transition in the early universe .

cosmic strings are line-like topological defects that are likely to emerge through phase transitions with spontaneous symmetry breaking .

the exchange correlation between electrons was treated with generalized gradient approximation in the perdewburke-ernzerhof form .

the electron exchangecorrelation functional was treated using the generalized gradient approximation in the form proposed by perdew , burke , and ernzerhof .

a single defect in pbg environments can possess localized modes for frequencies inside the gap .

as it was stated earlier single defects in pbg environments can possess localized modes for frequencies inside the gap .

in this case , sequence detection can be performed using recurrent neural networks .

sequence detection can be performed using recurrent neural networks .

the attractors of iterated function systems , a basic tool is the box-covering method .

the attractors of iterated function systems , a basic tool is the box covering method , that can be applied to networks .

note that here the trispectrum terms may contribute an even larger correction on small scales .

note that on very small scales , the non-gaussian contribution from the trispectrum might be significant .

lattice-boltzmann simulations of liquid-gas and binary fluid mixtures .

lattice boltzmann simulation of nonideal fluids .

it is based on the bsp model and adopts the vertex-centric paradigm with explicit messages to support scalable big graph processing .

it adopts the bulksynchronous parallel model with explicit messages to let users implement graph algorithms in a vertex-centric way .

for our cnn , we use 300-dimensional word2vec word embeddings trained on googlenews dataset 3 , and 128 feature maps with filter width .

we use the 300-dimension word2vec embeddings pretrained on google news dataset with about 100 billion words .

deep convolutional neural networks have achieved great success in computer vision related tasks such as image classification , and so on .

in particular , convolutional neural networks have been very successful for image classification .

gauge theories on non-commutative spaces can arise in certain limits of string theory .

indeed , noncommutative field theories can be derived from string theory by the seiberg-witten limit .

deep convolutional neural networks have achieved great success in various computer vision tasks such as image classification .

convolutional neural networks provide state-of-the-art results for many machine learning challenges , such as image classification .

a classic algorithm called the probabilistic classifier chain is a state-of-the-art csmlc algorithm .

a classic algorithm called probabilistic classifier chain , an algorithm that extends from cc , is a state-of-the-art csmlc algorithm .

a method to prove that some families are fc , 2 .

a method to prove that some families are not fc , 3 .

since the diffraction-limited region of an approximate bessel beam extends over large propagation distances , multiple trapping of particles with a single beam becomes possible .

for example , simultaneous trapping of several particles over large axial distances is possible by using just one single bessel beam .

model-based test generation techniques can target specific scenarios or requirements more effectively .

model-based test generation techniques can target specific use cases or requirements far more efficiently and effectively .

an isomorphism is a morphism with a continuous inverse .

which satisfies φ is called a sequential isomorphism .

physical states also exist when solely scalar multiplets are concerned .

physical states also exit when solely scalar multiplets are concerned .

the air-suspended nanotubes are synthesized by alcohol chemical vapor deposition .

the nanotubes are synthesized by alcohol chemical vapor deposition from catalyst particles placed near the trenches .

we select the same set of 871 subjects used in , comprising 403 individuals with asd and 468 healthy controls acquired at 20 different sites .

we select the same set of 871 subjects used by abraham et al that met the imaging quality and phenotypic information criteria , comprising 403 individuals with asd and 468 healthy controls .

it has indeed been shown in zou that the lasso estimator does not have the oracle property even in the finite parameter setting .

as a consequence , zou shows that the adaptive lasso has the oracle property under some regularity conditions .

a possible solution to this sensitivity problem is the design of a special sensing chamber that controls humidity and delivers the gas to the sensors under predefined conditions .

a possible solution to this sensitivity problem is a design of a special sensing chamber that controls humidity and delivers the gas to the sensors under predefined conditions .

the flow-motion network was trained for 750k steps with the adam optimizer .

the network was trained using an adam optimizer for gradient descent .

in fact , the direct implementation is known to be slow for practical settings of σs .

in general , the direct implementation is slow for practical settings of σ s .

deep convolutional neural networks have made significant progress in classification problems , which have shown to generate good results when provided sufficient data .

convolutional neural networks , alexnet being some famous examples , have demonstrated impressive performance on object detection tasks and are considered particularly well suited for feature extraction and classification .

we use the metropolis algorithm to simulate two-dimensional ising system .

the monte carlo simulation that we perform employs the standard metropolis algorithm .

the conditions have recently proved important in constructing electromagnetic cloaking structures .

the db conditions have been shown to play a central role in electromagnetic cloaking problems .

in quantum mechanics h is the planck constant .

the firmest thing of all in quantum mechanics is the formalism itself .

the benefits of network coding for distributed storage were first formalized by the work of dimakis et al .

the benefits of network coding for distributed storage has been first formalized by the work of dimakis et al .

from the arguments given in this paper , one can also see that the pauli-villars regularization and dimensional regularization gives the same result on the transverse anomaly of the axial vector and vector current .

at this point we remark that instead of pauli-villars regularization , one can also employ other regularization schemes such as dimensional regularization to calculate the transverse anomalies .

in , izumi studied certain explicit examples of endomorphisms of cuntz algebras motivated by subfactor theory .

in particular , localized endomorphisms of the cuntz algebras were investigated in the framework of the jones index theory in .

the thick lines represent the phase boundaries .

the thick lines show the phase boundaries .

asymptotic distribution and variance calculations were recently developed for m-estimators in this regime , el karoui , 2013 , donoho and montanari , 2013 .

it was previously shown that the asymptotic distribution of m-estimators in this design is nontrivial , donoho and montanari , 2013 , el karoui , 2013 .

multi-task learning for neural networks in general and within nlp specifically has been widely studied .

multi-task learning has been extensively studied in the literature , with applications to a wide set of problems ranging from natural language processing .

this is because each nucleon in the projectile does not excite pion production independently .

this indicates each nucleon in the projectile excites pion production almost dependently .

generative adversarial network is a class of deep learning algorithms that is used for generative modeling .

generative adversarial networks are a class of artificial intelligence algorithms used in unsupervised machine learning , which are introduced by .

the asterisk denotes additional information in the text .

the asterisk denotes that this result is strictly valid only when also a time average is considered .

the lower plot indicates the tail of the distribution .

the high-k tail of the distribution is shown in the lower plot .

note that if an energy estimate with bounding properties is used , then a similar bounding of the error in the quantity of interest can be obtained .

note that if we use an energy estimate with bounding properties , then the error estimate for the quantity of interest is bounded .

the belle detector is a large-solid-angle spectrometer based on a 1 5 t superconducting solenoid magnet .

the belle detector is a large-solid-angle magnetic spectrometer that consists of a three-layer silicon vertex detector .

the ultracold bose gas in optical lattices is well described by the bose-hubbard model .

in particular , bosons in optical lattices are near ideal realizations of the bose-hubbard model .

the generic architectures of the homogeneously encoded and heterogeneously encoded asynchronous rcas are given in and the reader is referred to the same for details .

the circuit architectures of the homogeneously and heterogeneously encoded asynchronous adders are given in , and the interested reader is referred to the same for details .

deep neural networks have shown improvement in state-of-the-art in different tasks , such as image classification .

deep neural networks have been adopted to improve the performance of state-of-the-arts on a wide variety of tasks in computer vision , including image classification .

specifically , convolutional neural networks have proved its effectiveness in a wide range of applications such as object recognition .

deep neural networks have significantly improved the state of the art on many supervised tasks .

summation formulas for the penalization terms .

discrete duality formulas for the convection terms .

cluster algebras form a large , axiomatically defined class of algebras , introduced by fomin and zelevinsky .

cluster algebras were introduced by fomin and zelevinsky in the series of papers .

our approach relies on the theory of graph signal processing .

we do so by building on the theory of graph signal processing .

more recently , graph attention networks have been introduced as an effective alternative for graph data modeling .

recently , graph convolutional networks have been widely studied for graph representation and learning .

although string theory is a strong candidate of it , the dynamics of the fermion states in string theories has not yet been extensively studied .

more importantly , string theory is a perfectly quantum mechanical theory which does include gravity .

such an asymmetry is the remnant of the partonic asymmetry .

this asymmetry is the origin of the finite real part of the soft mode .

the generalized gradient approximation according to perdewburke-ernzerhof was employed for both the generation of the pseudopotentials and the exchange-correlation functional .

the generalized gradient approximation of perdew-burkeernzerhof 30 type was employed for the exchange-correlation energy .

convolutional neural networks have achieved remarkable successes for various tasks , such as object recognition and so on .

convolutional neural networks have recently provided state of the art results for several recognition tasks including object recognition .

the encoder in the epva method is initialized with the vgg network pretrained on imagenet .

the network is initialized with the weights from the pretrained resnet-101 model on imagenet .

these networks have shown impressive results on computer vision tasks such as image labeling and object detection .

these visual representations have been shown to be effective on a wide range of computer vision tasks .

deep neural networks have achieved state-of-the-art performance on tasks such as image recognition in the last few years .

with the recent advances in deep convolutional neural networks , numerous image generation methods have achieved the state-of-the-art results .

the result of the ks-test is the probability of null-hypothesis that two distributions of the indicator are generated from the same population .

the result of the ks-test is the probability of the null-hypothesis that two distributions of the indicator are generated from the same population .

convolutional neural networks have improved the performance of image classification significantly .

object recognition has made significant progress with convolutional neural networks .

it is natural to conjecture that this is the unique non-zero irreducible object of this category .

a natural conjecture to make is the following .

hu et al propose the squeezeand-excitation block that adaptively recalibrates channelwise feature responses by explicitly modelling interdependencies between channels .

recently , hu et al proposes the squeeze-andexcitation block , which adaptively recalibrates channelwise feature responses by explicitly modelling interdependencies between channels .

the saturation below 1gev is the result of the fixed age of the cr particles , which is caused by the dynamical arms .

this contribution is negative , and is called normal saturation .

for c sb , we can use the floyd-warshall algorithm to compute all-pairs shortest paths in a graph .

the floyd-warshall algorithm is usually used to calculate all the pairs-shortest-paths in 1 g and 2 g .

set a contact lie group is a dimension n is called a legendrian submanifold of g .

this submanifold is the only tangentially degenerate submanifold without singularities in p n .

a different proof , based on the jones polynomial , follows from .

one proof which uses directly this relation to the jones polynomial is given in .

see labourie for definitions and more detailed discussions of anosov representations .

in this section , we recall the definition and basic properties of anosov representations , see labourie for further details .

phillips , university of arizona press , tuscon , pp .

gehrels , university of arizona press , tucson , pp .

there is growing evidence that all the known perturbative ten dimensional superstring theories are limits of an eleven dimensional theory called m theory .

the dualities between various superstring theories and m theory provide strong constraints on their effective actions .

since the higgs field is a component of the four-dimensional gluon field , no linear divergence of the higgs self-energy can occur due to the slavnov-taylor identities of the four-dimensional theory .

the higgs field is the responsible for triggering this ewsb mechanism .

we show that taking into account adiabatic expansion losses it is possible to describe the spectral evolution during the decay phase of individual pulses in long grbs .

finally , we argue that the observed spectral behavior of long pulses , during the grb decay phase of the light curve , can be described taking into account the energy loss for adiabatic expansion .

if there is no overshoot , which happens in particular in models with continuous asset prices , then the growth-optimal portfolio is indeed optimal .

if the objective is somewhat altered into minimizing expected market time , as we shall define below , then the growth-optimal portfolio is indeed optimal .

the ellipses denote the terms that are suppressed by positive powers of b .

where ellipses denote higher-twist contributions , ψ is a quark field and m is the nucleon mass .

various combinations of optical oscillations and tunneling ( bo , do and zt ) are formed as demonstrated on the phase diagram .

various superpositions of optical oscillations and zt are shown on the phase diagram .

kirkpatrick et al proposes elastic weight consolidation whose objective is to minimize the change of weights that are important to previous tasks through the use of a quadratic constraint .

recently , kirkpatrick et al proposed elastic weight consolidation , a quadratic penalty on the difference between the parameters for the new and the old task .

goodfellow et al claim that , in the case of neural networks , there is an excess of linearity in the behaviour of the networks .

goodfellow et al validate that practical attack in deep neural networks is possible because these models are locally linear .

we simulate the performance of our diva profiling mechanism using a modified version of ramulator .

we evaluate voltron using ramulator , integrated with a multicore performance simulator .

the aforementioned narrowband systems use measurements of the radio to extract information about people in the surrounding environment and therefore , such networks are referred to as rf sensor networks .

in general , these systems utilize received signal strength measurements of the radio for gaining situational awareness of the surrounding environment and therefore , they are commonly referred to as rf sensor networks .

ei buchbinder , il buchbinder , sm kuzenko , phys .

il buchbinder , ei buchbinder , sm kuzenko , ba ovrut , phys .

cluster algebras have been introduced by fomin and zelevinsky in in the context of total positivity and canonical bases in lie theory .

cluster algebras were introduced by fomin and zelevinsky in in order to study total positivity and canonical bases in semisimple groups .

our proposed method is implemented based on the deep learning library pytorch .

we have implemented our method by using pytorch , which is one of the most famous machine learning library .

since only the weak convergence was obtained in , no convergence rate was provided .

however , since only the weak convergence was obtained in , no convergence rate was provided there .

recently , deep convolutional neural networks have attracted much research attention in visual recognition , largely due to their excellent performance .

deep convolutional neural networks have been successful in many computer vision tasks including image classification .

wang et al propose a recurrent fully convolutional network for saliency detection that includes priors to correct initial saliency detection errors .

wang et al generated saliency prior maps using low-level cues and further exploited it to guide the prediction of saliency recurrently .

we implement the proposed model using pytorch on a single nvidia p40 gpu .

we implement the deep affinity network using the pytorch framework .

like many previous researches , this paper compares the performance of its proposed method with other individual clustering methods and cluster ensemble methods by using standard data sets and their real classes .

like many pervious researches , this paper compares the performance of its proposed method with other individual clustering methods and cluster ensemble methods by using standard datasets and their real classes .

to minimize the error of linear queries under differential privacy requirements , several methods try to build a synopsis of the original database , such as fourier transformations .

to minimize the error of linear queries under differential privacy requirements , several methods try to build a synopsis of the original database , such as fourier transformations and hierarchical trees .

starting with the work of li and haldane , the behavior of entanglement spectrum of two-dimensional systems has been extensively studied .

starting with the work of li and haldane , the behavior of the entanglement spectrum of twodimensional systems has been extensively studied .

silicon is the most widely used semiconductor in microelectronics .

silicon is a promising candidate for constructing a cavity-phoniton system .

recurrent neural networks have been gaining popularity in the machine learning community due to their impressive performance on tasks such as machine translation .

deep neural networks have become an extremely popular learning technique , with significant deployment in a wide variety of practical domains such as image classification .

socher et al , 2012 , uses a recursive neural network in relation extraction , and further use lstm .

miwa et al , used long short term memory based rnns for relation classification .