title stringlengths 7 239 | abstract stringlengths 7 2.76k | cs int64 0 1 | phy int64 0 1 | math int64 0 1 | stat int64 0 1 | quantitative biology int64 0 1 | quantitative finance int64 0 1 |
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Large-scale Nonlinear Variable Selection via Kernel Random Features | We propose a new method for input variable selection in nonlinear regression.
The method is embedded into a kernel regression machine that can model general
nonlinear functions, not being a priori limited to additive models. This is the
first kernel-based variable selection method applicable to large datasets. It
sid... | 0 | 0 | 0 | 1 | 0 | 0 |
Couple microscale periodic patches to simulate macroscale emergent dynamics | This article proposes a new way to construct computationally efficient
`wrappers' around fine scale, microscopic, detailed descriptions of dynamical
systems, such as molecular dynamics, to make predictions at the macroscale
`continuum' level. It is often significantly easier to code a microscale
simulator with period... | 0 | 0 | 1 | 0 | 0 | 0 |
Determinantal Point Processes for Mini-Batch Diversification | We study a mini-batch diversification scheme for stochastic gradient descent
(SGD). While classical SGD relies on uniformly sampling data points to form a
mini-batch, we propose a non-uniform sampling scheme based on the Determinantal
Point Process (DPP). The DPP relies on a similarity measure between data points
and... | 1 | 0 | 0 | 1 | 0 | 0 |
Proton-induced halo formation in charged meteors | Despite a very long history of meteor science, our understanding of meteor
ablation and its shocked plasma physics is still far from satisfactory as we
are still missing the microphysics of meteor shock formation and its plasma
dynamics. Here we argue that electrons and ions in the meteor plasma above
$\sim$100 km al... | 0 | 1 | 0 | 0 | 0 | 0 |
Generalised Seiberg-Witten equations and almost-Hermitian geometry | In this article, we study a generalisation of the Seiberg-Witten equations,
replacing the spinor representation with a hyperKahler manifold equipped with
certain symmetries. Central to this is the construction of a (non-linear) Dirac
operator acting on the sections of the non-linear fibre-bundle. For hyperKahler
mani... | 0 | 0 | 1 | 0 | 0 | 0 |
Enhanced Photon Traps for Hyper-Kamiokande | Hyper-Kamiokande, the next generation large water Cherenkov detector in
Japan, is planning to use approximately 80,000 20-inch photomultiplier tubes
(PMTs). They are one of the major cost factors of the experiment. We propose a
novel enhanced photon trap design based on a smaller and more economical PMT in
combinatio... | 0 | 1 | 0 | 0 | 0 | 0 |
A Deep Reinforcement Learning Chatbot (Short Version) | We present MILABOT: a deep reinforcement learning chatbot developed by the
Montreal Institute for Learning Algorithms (MILA) for the Amazon Alexa Prize
competition. MILABOT is capable of conversing with humans on popular small talk
topics through both speech and text. The system consists of an ensemble of
natural lan... | 0 | 0 | 0 | 1 | 0 | 0 |
A Recurrent Neural Network for Sentiment Quantification | Quantification is a supervised learning task that consists in predicting,
given a set of classes C and a set D of unlabelled items, the prevalence (or
relative frequency) p(c|D) of each class c in C. Quantification can in
principle be solved by classifying all the unlabelled items and counting how
many of them have b... | 0 | 0 | 0 | 1 | 0 | 0 |
Data Noising as Smoothing in Neural Network Language Models | Data noising is an effective technique for regularizing neural network
models. While noising is widely adopted in application domains such as vision
and speech, commonly used noising primitives have not been developed for
discrete sequence-level settings such as language modeling. In this paper, we
derive a connectio... | 1 | 0 | 0 | 0 | 0 | 0 |
Optical Flow-based 3D Human Motion Estimation from Monocular Video | We present a generative method to estimate 3D human motion and body shape
from monocular video. Under the assumption that starting from an initial pose
optical flow constrains subsequent human motion, we exploit flow to find
temporally coherent human poses of a motion sequence. We estimate human motion
by minimizing ... | 1 | 0 | 0 | 0 | 0 | 0 |
Quasi-ordered Rings | A quasi-order is a binary, reflexive and transitive relation. In the Journal
of Pure and Applied Algebra 45 (1987), S.M. Fakhruddin introduced the notion of
(totally) quasi-ordered fields and showed that each such field is either an
ordered field or else a valued field. Hence, quasi-ordered fields are very well
suite... | 0 | 0 | 1 | 0 | 0 | 0 |
Mean-Field Controllability and Decentralized Stabilization of Markov Chains, Part I: Global Controllability and Rational Feedbacks | In this paper, we study the controllability and stabilizability properties of
the Kolmogorov forward equation of a continuous time Markov chain (CTMC)
evolving on a finite state space, using the transition rates as the control
parameters. Firstly, we prove small-time local and global controllability from
and to stric... | 1 | 0 | 1 | 0 | 0 | 0 |
Sharp total variation results for maximal functions | In this article, we prove some total variation inequalities for maximal
functions. Our results deal with two possible generalizations of the results
contained in Aldaz and Pérez Lázaro's work, one of whose considers a
variable truncation of the maximal function, and the other one interpolates the
centered and the unc... | 0 | 0 | 1 | 0 | 0 | 0 |
Optimal Bipartite Network Clustering | We study bipartite community detection in networks, or more generally the
network biclustering problem. We present a fast two-stage procedure based on
spectral initialization followed by the application of a pseudo-likelihood
classifier twice. Under mild regularity conditions, we establish the weak
consistency of the... | 1 | 0 | 0 | 1 | 0 | 0 |
End-to-end Recurrent Neural Network Models for Vietnamese Named Entity Recognition: Word-level vs. Character-level | This paper demonstrates end-to-end neural network architectures for
Vietnamese named entity recognition. Our best model is a combination of
bidirectional Long Short-Term Memory (Bi-LSTM), Convolutional Neural Network
(CNN), Conditional Random Field (CRF), using pre-trained word embeddings as
input, which achieves an ... | 1 | 0 | 0 | 0 | 0 | 0 |
The Reduced PC-Algorithm: Improved Causal Structure Learning in Large Random Networks | We consider the task of estimating a high-dimensional directed acyclic graph,
given observations from a linear structural equation model with arbitrary noise
distribution. By exploiting properties of common random graphs, we develop a
new algorithm that requires conditioning only on small sets of variables. The
propo... | 0 | 0 | 0 | 1 | 1 | 0 |
Theoretical analysis of the electron bridge process in $^{229}$Th$^{3+}$ | We investigate the deexcitation of the $^{229}$Th nucleus via the excitation
of an electron. Detailed calculations are performed for the enhancement of the
nuclear decay width due to this so called electron bridge (EB) compared to the
direct photoemission from the nucleus. The results are obtianed for triply
ionized ... | 0 | 1 | 0 | 0 | 0 | 0 |
Memory in de Sitter space and BMS-like supertranslations | It is well known that the memory effect in flat spacetime is parametrized by
the BMS supertranslation. We investigate the relation between the memory effect
and diffeomorphism in de Sitter spacetime. We find that gravitational memory is
parametrized by a BMS-like supertranslation in the static patch of de Sitter
spac... | 0 | 1 | 0 | 0 | 0 | 0 |
Data-Driven Estimation Of Mutual Information Between Dependent Data | We consider the problem of estimating mutual information between dependent
data, an important problem in many science and engineering applications. We
propose a data-driven, non-parametric estimator of mutual information in this
paper. The main novelty of our solution lies in transforming the data to
frequency domain... | 1 | 0 | 0 | 1 | 0 | 0 |
Wigner functions for gauge equivalence classes of unitary irreducible representations of noncommutative quantum mechanics | While Wigner functions forming phase space representation of quantum states
is a well-known fact, their construction for noncommutative quantum mechanics
(NCQM) remains relatively lesser known, in particular with respect to gauge
dependencies. This paper deals with the construction of Wigner functions of
NCQM for a s... | 0 | 0 | 1 | 0 | 0 | 0 |
Segmentation of Intracranial Arterial Calcification with Deeply Supervised Residual Dropout Networks | Intracranial carotid artery calcification (ICAC) is a major risk factor for
stroke, and might contribute to dementia and cognitive decline. Reliance on
time-consuming manual annotation of ICAC hampers much demanded further research
into the relationship between ICAC and neurological diseases. Automation of
ICAC segme... | 1 | 0 | 0 | 0 | 0 | 0 |
HTMoL: full-stack solution for remote access, visualization, and analysis of Molecular Dynamics trajectory data | The field of structural bioinformatics has seen significant advances with the
use of Molecular Dynamics (MD) simulations of biological systems. The MD
methodology has allowed to explain and discover molecular mechanisms in a wide
range of natural processes. There is an impending need to readily share the
ever-increas... | 1 | 0 | 0 | 0 | 0 | 0 |
General auction method for real-valued optimal transport | The auction method developed by Bertsekas in the late 1970s is a relaxation
technique for solving integer-valued assignment problems. It resembles a
competitive bidding process, where unsatisfied persons (bidders) attempt to
claim the objects (lots) offering the best value. By transforming
integer-valued transport pr... | 1 | 0 | 1 | 0 | 0 | 0 |
Force sensing with an optically levitated charged nanoparticle | Levitated optomechanics is showing potential for precise force measurements.
Here, we report a case study, to show experimentally the capacity of such a
force sensor. Using an electric field as a tool to detect a Coulomb force
applied onto a levitated nanosphere. We experimentally observe the spatial
displacement of ... | 0 | 1 | 0 | 0 | 0 | 0 |
Unveiling Eilenberg-type Correspondences: Birkhoff's Theorem for (finite) Algebras + Duality | The purpose of the present paper is to show that: Eilenberg-type
correspondences = Birkhoff's theorem for (finite) algebras + duality. We
consider algebras for a monad T on a category D and we study (pseudo)varieties
of T-algebras. Pseudovarieties of algebras are also known in the literature as
varieties of finite al... | 1 | 0 | 1 | 0 | 0 | 0 |
Detecting transit signatures of exoplanetary rings using SOAP3.0 | CONTEXT. It is theoretically possible for rings to have formed around
extrasolar planets in a similar way to that in which they formed around the
giant planets in our solar system. However, no such rings have been detected to
date.
AIMS: We aim to test the possibility of detecting rings around exoplanets by
investiga... | 0 | 1 | 0 | 0 | 0 | 0 |
MatlabCompat.jl: helping Julia understand Your Matlab/Octave Code | Scientific legacy code in MATLAB/Octave not compatible with modernization of
research workflows is vastly abundant throughout academic community.
Performance of non-vectorized code written in MATLAB/Octave represents a major
burden. A new programming language for technical computing Julia, promises to
address these i... | 1 | 0 | 0 | 0 | 0 | 0 |
Extending the topological analysis and seeking the real-space subsystems in non-Coulombic systems with homogeneous potential energy functions | It is customary to conceive the interactions of all the constituents of a
molecular system, i.e. electrons and nuclei, as Coulombic. However, in a more
detailed analysis one may always find small but non-negligible non-Coulombic
interactions in molecular systems originating from the finite size of nuclei,
magnetic in... | 0 | 1 | 0 | 0 | 0 | 0 |
Deep Uncertainty Surrounding Coastal Flood Risk Projections: A Case Study for New Orleans | Future sea-level rise drives severe risks for many coastal communities.
Strategies to manage these risks hinge on a sound characterization of the
uncertainties. For example, recent studies suggest that large fractions of the
Antarctic ice sheet (AIS) may rapidly disintegrate in response to rising global
temperatures,... | 0 | 1 | 0 | 0 | 0 | 0 |
Bounds on the Approximation Power of Feedforward Neural Networks | The approximation power of general feedforward neural networks with piecewise
linear activation functions is investigated. First, lower bounds on the size of
a network are established in terms of the approximation error and network depth
and width. These bounds improve upon state-of-the-art bounds for certain
classes... | 0 | 0 | 0 | 1 | 0 | 0 |
Non-classification of free Araki-Woods factors and $τ$-invariants | We define the standard Borel space of free Araki-Woods factors and prove that
their isomorphism relation is not classifiable by countable structures. We also
prove that equality of $\tau$-topologies, arising as invariants of type III
factors, as well as coycle and outer conjugacy of actions of abelian groups on
free ... | 0 | 0 | 1 | 0 | 0 | 0 |
Data-Driven Learning and Planning for Environmental Sampling | Robots such as autonomous underwater vehicles (AUVs) and autonomous surface
vehicles (ASVs) have been used for sensing and monitoring aquatic environments
such as oceans and lakes. Environmental sampling is a challenging task because
the environmental attributes to be observed can vary both spatially and
temporally, ... | 1 | 0 | 0 | 0 | 0 | 0 |
Global spectral graph wavelet signature for surface analysis of carpal bones | In this paper, we present a spectral graph wavelet approach for shape
analysis of carpal bones of human wrist. We apply a metric called global
spectral graph wavelet signature for representation of cortical surface of the
carpal bone based on eigensystem of Laplace-Beltrami operator. Furthermore, we
propose a heurist... | 1 | 0 | 0 | 0 | 0 | 0 |
Learning Rates of Regression with q-norm Loss and Threshold | This paper studies some robust regression problems associated with the
$q$-norm loss ($q\ge1$) and the $\epsilon$-insensitive $q$-norm loss in the
reproducing kernel Hilbert space. We establish a variance-expectation bound
under a priori noise condition on the conditional distribution, which is the
key technique to m... | 0 | 0 | 1 | 1 | 0 | 0 |
Instability, rupture and fluctuations in thin liquid films: Theory and computations | Thin liquid films are ubiquitous in natural phenomena and technological
applications. They have been extensively studied via deterministic hydrodynamic
equations, but thermal fluctuations often play a crucial role that needs to be
understood. An example of this is dewetting, which involves the rupture of a
thin liqui... | 0 | 1 | 0 | 0 | 0 | 0 |
Fractional Patlak-Keller-Segel equations for chemotactic superdiffusion | The long range movement of certain organisms in the presence of a
chemoattractant can be governed by long distance runs, according to an
approximate Levy distribution. This article clarifies the form of biologically
relevant model equations: We derive Patlak-Keller-Segel-like equations
involving nonlocal, fractional ... | 0 | 1 | 0 | 0 | 0 | 0 |
Adaptive Risk Bounds in Univariate Total Variation Denoising and Trend Filtering | We study trend filtering, a relatively recent method for univariate
nonparametric regression. For a given positive integer $r$, the $r$-th order
trend filtering estimator is defined as the minimizer of the sum of squared
errors when we constrain (or penalize) the sum of the absolute $r$-th order
discrete derivatives ... | 0 | 0 | 1 | 1 | 0 | 0 |
Assessment of First-Principles and Semiempirical Methodologies for Absorption and Emission Energies of Ce$^{3+}$-Doped Luminescent Materials | In search of a reliable methodology for the prediction of light absorption
and emission of Ce$^{3+}$-doped luminescent materials, 13 representative
materials are studied with first-principles and semiempirical approaches. In
the first-principles approach, that combines constrained density-functional
theory and $\Delt... | 0 | 1 | 0 | 0 | 0 | 0 |
Regularizing deep networks using efficient layerwise adversarial training | Adversarial training has been shown to regularize deep neural networks in
addition to increasing their robustness to adversarial examples. However, its
impact on very deep state of the art networks has not been fully investigated.
In this paper, we present an efficient approach to perform adversarial training
by pert... | 1 | 0 | 0 | 1 | 0 | 0 |
Improving Dynamic Analysis of Android Apps Using Hybrid Test Input Generation | The Android OS has become the most popular mobile operating system leading to
a significant increase in the spread of Android malware. Consequently, several
static and dynamic analysis systems have been developed to detect Android
malware. With dynamic analysis, efficient test input generation is needed in
order to t... | 1 | 0 | 0 | 0 | 0 | 0 |
Process Monitoring Using Maximum Sequence Divergence | Process Monitoring involves tracking a system's behaviors, evaluating the
current state of the system, and discovering interesting events that require
immediate actions. In this paper, we consider monitoring temporal system state
sequences to help detect the changes of dynamic systems, check the divergence
of the sys... | 0 | 0 | 0 | 1 | 0 | 0 |
Some generalizations of Kannan's theorems via $σ_c$-function | In this article we go on to discuss about various proper extensions of
Kannan's two different fixed point theorems, introducing the new concept of
$\sigma_c$-function; which is independent of the three notions of simulation
function, manageable functions and R-functions. These results are the analogous
to some well k... | 0 | 0 | 1 | 0 | 0 | 0 |
On Exact Sequences of the Rigid Fibrations | In 2002, Biss investigated on a kind of fibration which is called rigid
covering fibration (we rename it by rigid fibration) with properties similar to
covering spaces. In this paper, we obtain a relation between arbitrary
topological spaces and its rigid fibrations. Using this relation we obtain a
commutative diagra... | 0 | 0 | 1 | 0 | 0 | 0 |
Analytic Gradients for Complete Active Space Pair-Density Functional Theory | Analytic gradient routines are a desirable feature for quantum mechanical
methods, allowing for efficient determination of equilibrium and transition
state structures and several other molecular properties. In this work, we
present analytical gradients for multiconfiguration pair-density functional
theory (MC-PDFT) w... | 0 | 1 | 0 | 0 | 0 | 0 |
Northern sky Galactic Cosmic Ray anisotropy between 10-1000 TeV with the Tibet Air Shower Array | We report the analysis of the $10-1000$ TeV large-scale sidereal anisotropy
of Galactic cosmic rays (GCRs) with the data collected by the Tibet Air Shower
Array from October, 1995 to February, 2010. In this analysis, we improve the
energy estimate and extend the declination range down to $-30^{\circ}$. We find
that t... | 0 | 1 | 0 | 0 | 0 | 0 |
Count-ception: Counting by Fully Convolutional Redundant Counting | Counting objects in digital images is a process that should be replaced by
machines. This tedious task is time consuming and prone to errors due to
fatigue of human annotators. The goal is to have a system that takes as input
an image and returns a count of the objects inside and justification for the
prediction in t... | 1 | 0 | 0 | 1 | 0 | 0 |
A robust inverse scattering transform for the focusing nonlinear Schrödinger equation | We propose a modification of the standard inverse scattering transform for
the focusing nonlinear Schrödinger equation (also other equations by natural
generalization) formulated with nonzero boundary conditions at infinity. The
purpose is to deal with arbitrary-order poles and potentially severe spectral
singulariti... | 0 | 1 | 0 | 0 | 0 | 0 |
Admissible Bayes equivariant estimation of location vectors for spherically symmetric distributions with unknown scale | This paper investigates estimation of the mean vector under invariant
quadratic loss for a spherically symmetric location family with a residual
vector with density of the form $
f(x,u)=\eta^{(p+n)/2}f(\eta\{\|x-\theta\|^2+\|u\|^2\}) $, where $\eta$ is
unknown. We show that the natural estimator $x$ is admissible for... | 0 | 0 | 1 | 1 | 0 | 0 |
A proof theoretic study of abstract termination principles | We define a variety of abstract termination principles which form
generalisations of simplification orders, and investigate their computational
content. Simplification orders, which include the well-known multiset and
lexicographic path orderings, are important techniques for proving that
computer programs terminate.... | 1 | 0 | 1 | 0 | 0 | 0 |
Why exomoons must be rare? | The problem of the search for the satellites of the exoplanets (exomoons) is
discussed recently. There are very many satellites in our Solar System. But in
contrary of our Solar system, exoplanets have significant eccentricity. In
process of planetary migration, exoplanets can cross some resonances with
following gro... | 0 | 1 | 0 | 0 | 0 | 0 |
Propagation of regularity in $L^p$-spaces for Kolmogorov type hypoelliptic operators | Consider the following Kolmogorov type hypoelliptic operator $$ \mathscr
L_t:=\mbox{$\sum_{j=2}^n$}x_j\cdot\nabla_{x_{j-1}}+{\rm Tr} (a_t
\cdot\nabla^2_{x_n}), $$ where $n\geq 2$, $x=(x_1,\cdots,x_n)\in(\mathbb R^d)^n
=\mathbb R^{nd}$ and $a_t$ is a time-dependent constant symmetric $d\times
d$-matrix that is uniform... | 0 | 0 | 1 | 0 | 0 | 0 |
On Relation between Constraint Answer Set Programming and Satisfiability Modulo Theories | Constraint answer set programming is a promising research direction that
integrates answer set programming with constraint processing. It is often
informally related to the field of satisfiability modulo theories. Yet, the
exact formal link is obscured as the terminology and concepts used in these two
research areas ... | 1 | 0 | 0 | 0 | 0 | 0 |
The w-effect in interferometric imaging: from a fast sparse measurement operator to super-resolution | Modern radio telescopes, such as the Square Kilometre Array (SKA), will probe
the radio sky over large fields-of-view, which results in large w-modulations
of the sky image. This effect complicates the relationship between the measured
visibilities and the image under scrutiny. In algorithmic terms, it gives rise
to ... | 0 | 1 | 0 | 0 | 0 | 0 |
Large Scale Graph Learning from Smooth Signals | Graphs are a prevalent tool in data science, as they model the inherent
structure of the data. They have been used successfully in unsupervised and
semi-supervised learning. Typically they are constructed either by connecting
nearest samples, or by learning them from data, solving an optimization
problem. While graph... | 1 | 0 | 0 | 1 | 0 | 0 |
Power Plant Performance Modeling with Concept Drift | Power plant is a complex and nonstationary system for which the traditional
machine learning modeling approaches fall short of expectations. The
ensemble-based online learning methods provide an effective way to continuously
learn from the dynamic environment and autonomously update models to respond to
environmental... | 1 | 0 | 0 | 1 | 0 | 0 |
Does putting your emotions into words make you feel better? Measuring the minute-scale dynamics of emotions from online data | Studies of affect labeling, i.e. putting your feelings into words, indicate
that it can attenuate positive and negative emotions. Here we track the
evolution of individual emotions for tens of thousands of Twitter users by
analyzing the emotional content of their tweets before and after they
explicitly report having ... | 1 | 0 | 0 | 0 | 0 | 0 |
Axiomatizing Epistemic Logic of Friendship via Tree Sequent Calculus | This paper positively solves an open problem if it is possible to provide a
Hilbert system to Epistemic Logic of Friendship (EFL) by Seligman, Girard and
Liu. To find a Hilbert system, we first introduce a sound, complete and
cut-free tree (or nested) sequent calculus for EFL, which is an integrated
combination of Se... | 1 | 0 | 1 | 0 | 0 | 0 |
A novel approach to the Lindelöf hypothesis | Lindel{ö}f's hypothesis, one of the most important open problems in the
history of mathematics, states that for large $t$, Riemann's zeta function
$\zeta(\frac{1}{2}+it)$ is of order $O(t^{\varepsilon})$ for any
$\varepsilon>0$. It is well known that for large $t$, the leading order
asymptotics of the Riemann zeta fu... | 0 | 0 | 1 | 0 | 0 | 0 |
An Overview of Recent Solutions to and Lower Bounds for the Firing Synchronization Problem | Complex systems in a wide variety of areas such as biological modeling, image
processing, and language recognition can be modeled using networks of very
simple machines called finite automata. Connecting subsystems modeled using
finite automata into a network allows for more computational power. One such
network, cal... | 1 | 1 | 0 | 0 | 0 | 0 |
On Tackling the Limits of Resolution in SAT Solving | The practical success of Boolean Satisfiability (SAT) solvers stems from the
CDCL (Conflict-Driven Clause Learning) approach to SAT solving. However, from a
propositional proof complexity perspective, CDCL is no more powerful than the
resolution proof system, for which many hard examples exist. This paper
proposes a ... | 1 | 0 | 0 | 0 | 0 | 0 |
Penalized Estimation in Additive Regression with High-Dimensional Data | Additive regression provides an extension of linear regression by modeling
the signal of a response as a sum of functions of covariates of relatively low
complexity. We study penalized estimation in high-dimensional nonparametric
additive regression where functional semi-norms are used to induce smoothness
of compone... | 0 | 0 | 1 | 1 | 0 | 0 |
Towards Quality Advancement of Underwater Machine Vision with Generative Adversarial Networks | Underwater machine vision has attracted significant attention, but its low
quality has prevented it from a wide range of applications. Although many
different algorithms have been developed to solve this problem, real-time
adaptive methods are frequently deficient. In this paper, based on filtering
and the use of gen... | 1 | 0 | 0 | 0 | 0 | 0 |
Linking Sketches and Diagrams to Source Code Artifacts | Recent studies have shown that sketches and diagrams play an important role
in the daily work of software developers. If these visual artifacts are
archived, they are often detached from the source code they document, because
there is no adequate tool support to assist developers in capturing, archiving,
and retrievi... | 1 | 0 | 0 | 0 | 0 | 0 |
Parsimonious Data: How a single Facebook like predicts voting behaviour in multiparty systems | Recently, two influential PNAS papers have shown how our preferences for
'Hello Kitty' and 'Harley Davidson', obtained through Facebook likes, can
accurately predict details about our personality, religiosity, political
attitude and sexual orientation (Konsinski et al. 2013; Youyou et al 2015). In
this paper, we make... | 1 | 0 | 0 | 0 | 0 | 0 |
The Hidden Vulnerability of Distributed Learning in Byzantium | While machine learning is going through an era of celebrated success,
concerns have been raised about the vulnerability of its backbone: stochastic
gradient descent (SGD). Recent approaches have been proposed to ensure the
robustness of distributed SGD against adversarial (Byzantine) workers sending
poisoned gradient... | 0 | 0 | 0 | 1 | 0 | 0 |
walk2friends: Inferring Social Links from Mobility Profiles | The development of positioning technologies has resulted in an increasing
amount of mobility data being available. While bringing a lot of convenience to
people's life, such availability also raises serious concerns about privacy. In
this paper, we concentrate on one of the most sensitive information that can be
infe... | 1 | 0 | 0 | 0 | 0 | 0 |
An Optimal Algorithm for Online Unconstrained Submodular Maximization | We consider a basic problem at the interface of two fundamental fields:
submodular optimization and online learning. In the online unconstrained
submodular maximization (online USM) problem, there is a universe
$[n]=\{1,2,...,n\}$ and a sequence of $T$ nonnegative (not necessarily
monotone) submodular functions arriv... | 0 | 0 | 0 | 1 | 0 | 0 |
Modeling Grasp Motor Imagery through Deep Conditional Generative Models | Grasping is a complex process involving knowledge of the object, the
surroundings, and of oneself. While humans are able to integrate and process
all of the sensory information required for performing this task, equipping
machines with this capability is an extremely challenging endeavor. In this
paper, we investigat... | 1 | 0 | 0 | 1 | 0 | 0 |
Designing an Effective Metric Learning Pipeline for Speaker Diarization | State-of-the-art speaker diarization systems utilize knowledge from external
data, in the form of a pre-trained distance metric, to effectively determine
relative speaker identities to unseen data. However, much of recent focus has
been on choosing the appropriate feature extractor, ranging from pre-trained
$i-$vecto... | 1 | 0 | 0 | 0 | 0 | 0 |
Mining Application-aware Community Organization with Expanded Feature Subspaces from Concerned Attributes in Social Networks | Social networks are typical attributed networks with node attributes.
Different from traditional attribute community detection problem aiming at
obtaining the whole set of communities in the network, we study an
application-oriented problem of mining an application-aware community
organization with respect to specifi... | 1 | 1 | 0 | 0 | 0 | 0 |
A spin-gapped Mott insulator with the dimeric arrangement of twisted molecules Zn(tmdt)$_{2}$ | $^{13}$C nuclear magnetic resonance measurements were performed for a
single-component molecular material Zn(tmdt)$_{2}$, in which tmdt's form an
arrangement similar to the so-called ${\kappa}$-type molecular packing in
quasi-two-dimensional Mott insulators and superconductors. Detailed analysis of
the powder spectra... | 0 | 1 | 0 | 0 | 0 | 0 |
Li doping kagome spin liquid compounds | Herbertsmithite and Zn-doped barlowite are two compounds for experimental
realization of twodimensional gapped kagome spin liquid. Theoretically, it has
been proposed that charge doping a quantum spin liquid gives rise to exotic
metallic states, such as high-temperature superconductivity. However, one
recent experime... | 0 | 1 | 0 | 0 | 0 | 0 |
DxNAT - Deep Neural Networks for Explaining Non-Recurring Traffic Congestion | Non-recurring traffic congestion is caused by temporary disruptions, such as
accidents, sports games, adverse weather, etc. We use data related to real-time
traffic speed, jam factors (a traffic congestion indicator), and events
collected over a year from Nashville, TN to train a multi-layered deep neural
network. Th... | 0 | 0 | 0 | 1 | 0 | 0 |
Facets of a mixed-integer bilinear covering set with bounds on variables | We derive a closed form description of the convex hull of mixed-integer
bilinear covering set with bounds on the integer variables. This convex hull
description is completely determined by considering some orthogonal disjunctive
sets defined in a certain way. Our description does not introduce any new
variables. We a... | 0 | 0 | 1 | 0 | 0 | 0 |
Universal partial sums of Taylor series as functions of the centre of expansion | V. Nestoridis conjectured that if $\Omega$ is a simply connected subset of
$\mathbb{C}$ that does not contain $0$ and $S(\Omega)$ is the set of all
functions $f\in \mathcal{H}(\Omega)$ with the property that the set
$\left\{T_N(f)(z)\coloneqq\sum_{n=0}^N\dfrac{f^{(n)}(z)}{n!} (-z)^n : N =
0,1,2,\dots \right\}$ is den... | 0 | 0 | 1 | 0 | 0 | 0 |
Free Cooling of a Granular Gas in Three Dimensions | Granular gases as dilute ensembles of particles in random motion are not only
at the basis of elementary structure-forming processes in the universe and
involved in many industrial and natural phenomena, but also excellent models to
study fundamental statistical dynamics. A vast number of theoretical and
numerical in... | 0 | 1 | 0 | 0 | 0 | 0 |
The SCUBA-2 Ambitious Sky Survey: a catalogue of beam-sized sources in the Galactic longitude range 120 to 140 | The SCUBA-2 Ambitious Sky Survey (SASSy) is composed of shallow 850-$\umu$m
imaging using the Sub-millimetre Common-User Bolometer Array 2 (SCUBA-2) on the
James Clerk Maxwell Telescope. Here we describe the extraction of a catalogue
of beam-sized sources from a roughly $120\,{\rm deg}^2$ region of the Galactic
plane... | 0 | 1 | 0 | 0 | 0 | 0 |
A stable and optimally convergent LaTIn-Cut Finite Element Method for multiple unilateral contact problems | In this paper, we propose a novel unfitted finite element method for the
simulation of multiple body contact. The computational mesh is generated
independently of the geometry of the interacting solids, which can be
arbitrarily complex. The key novelty of the approach is the combination of
elements of the CutFEM tech... | 1 | 0 | 0 | 0 | 0 | 0 |
Non Fermi liquid behavior and continuously tunable resistivity exponents in the Anderson-Hubbard model at finite temperature | We employ a recently developed computational many-body technique to study for
the first time the half-filled Anderson-Hubbard model at finite temperature and
arbitrary correlation ($U$) and disorder ($V$) strengths. Interestingly, the
narrow zero temperature metallic range induced by disorder from the Mott
insulator ... | 0 | 1 | 0 | 0 | 0 | 0 |
Beyond Parity: Fairness Objectives for Collaborative Filtering | We study fairness in collaborative-filtering recommender systems, which are
sensitive to discrimination that exists in historical data. Biased data can
lead collaborative-filtering methods to make unfair predictions for users from
minority groups. We identify the insufficiency of existing fairness metrics and
propose... | 1 | 0 | 0 | 1 | 0 | 0 |
Blind Regression via Nearest Neighbors under Latent Variable Models | We consider the setup of nonparametric 'blind regression' for estimating the
entries of a large $m \times n$ matrix, when provided with a small, random
fraction of noisy measurements. We assume that all rows $u \in [m]$ and columns
$i \in [n]$ of the matrix are associated to latent features $x_1(u)$ and
$x_2(i)$ resp... | 0 | 0 | 1 | 1 | 0 | 0 |
Metalearning for Feature Selection | A general formulation of optimization problems in which various candidate
solutions may use different feature-sets is presented, encompassing supervised
classification, automated program learning and other cases. A novel
characterization of the concept of a "good quality feature" for such an
optimization problem is p... | 1 | 0 | 0 | 1 | 0 | 0 |
Variability-Aware Design for Energy Efficient Computational Artificial Intelligence Platform | Portable computing devices, which include tablets, smart phones and various
types of wearable sensors, experienced a rapid development in recent years. One
of the most critical limitations for these devices is the power consumption as
they use batteries as the power supply. However, the bottleneck of the power
saving... | 1 | 0 | 0 | 0 | 0 | 0 |
Quantifying Performance of Bipedal Standing with Multi-channel EMG | Spinal cord stimulation has enabled humans with motor complete spinal cord
injury (SCI) to independently stand and recover some lost autonomic function.
Quantifying the quality of bipedal standing under spinal stimulation is
important for spinal rehabilitation therapies and for new strategies that seek
to combine spi... | 1 | 0 | 0 | 1 | 0 | 0 |
A framework for on-line calibration of LINAC devices | General description of an on-line procedure of calibration for IGRT (Image
Guided Radiotherapy) is given. The algorithm allows to improve targeting cancer
by estimating its position in space and suggests appropriate correction of the
position of the patient. The description is given in the Geometric Algebra
language ... | 0 | 1 | 0 | 0 | 0 | 0 |
People on Media: Jointly Identifying Credible News and Trustworthy Citizen Journalists in Online Communities | Media seems to have become more partisan, often providing a biased coverage
of news catering to the interest of specific groups. It is therefore essential
to identify credible information content that provides an objective narrative
of an event. News communities such as digg, reddit, or newstrust offer
recommendation... | 1 | 0 | 0 | 1 | 0 | 0 |
Towards Provably Safe Mixed Transportation Systems with Human-driven and Automated Vehicles | Currently, we are in an environment where the fraction of automated vehicles
is negligibly small. We anticipate that this fraction will increase in coming
decades before if ever, we have a fully automated transportation system.
Motivated by this we address the problem of provable safety of mixed traffic
consisting of... | 1 | 0 | 0 | 0 | 0 | 0 |
Streaming kernel regression with provably adaptive mean, variance, and regularization | We consider the problem of streaming kernel regression, when the observations
arrive sequentially and the goal is to recover the underlying mean function,
assumed to belong to an RKHS. The variance of the noise is not assumed to be
known. In this context, we tackle the problem of tuning the regularization
parameter a... | 1 | 0 | 0 | 1 | 0 | 0 |
Estimating reducible stochastic differential equations by conversion to a least-squares problem | Stochastic differential equations (SDEs) are increasingly used in
longitudinal data analysis, compartmental models, growth modelling, and other
applications in a number of disciplines. Parameter estimation, however,
currently requires specialized software packages that can be difficult to use
and understand. This wor... | 0 | 0 | 0 | 1 | 0 | 0 |
Deep Tensor Encoding | Learning an encoding of feature vectors in terms of an over-complete
dictionary or a information geometric (Fisher vectors) construct is wide-spread
in statistical signal processing and computer vision. In content based
information retrieval using deep-learning classifiers, such encodings are
learnt on the flattened ... | 1 | 0 | 0 | 1 | 0 | 0 |
hMDAP: A Hybrid Framework for Multi-paradigm Data Analytical Processing on Spark | We propose hMDAP, a hybrid framework for large-scale data analytical
processing on Spark, to support multi-paradigm process (incl. OLAP, machine
learning, and graph analysis etc.) in distributed environments. The framework
features a three-layer data process module and a business process module which
controls the for... | 1 | 0 | 0 | 0 | 0 | 0 |
Robust Unsupervised Domain Adaptation for Neural Networks via Moment Alignment | A novel approach for unsupervised domain adaptation for neural networks is
proposed. It relies on metric-based regularization of the learning process. The
metric-based regularization aims at domain-invariant latent feature
representations by means of maximizing the similarity between domain-specific
activation distri... | 1 | 0 | 0 | 1 | 0 | 0 |
A Convolutional Neural Network For Cosmic String Detection in CMB Temperature Maps | We present in detail the convolutional neural network used in our previous
work to detect cosmic strings in cosmic microwave background (CMB) temperature
anisotropy maps. By training this neural network on numerically generated CMB
temperature maps, with and without cosmic strings, the network can produce
prediction ... | 0 | 1 | 0 | 0 | 0 | 0 |
Improving Palliative Care with Deep Learning | Improving the quality of end-of-life care for hospitalized patients is a
priority for healthcare organizations. Studies have shown that physicians tend
to over-estimate prognoses, which in combination with treatment inertia results
in a mismatch between patients wishes and actual care at the end of life. We
describe ... | 1 | 0 | 0 | 1 | 0 | 0 |
Scalable Online Convolutional Sparse Coding | Convolutional sparse coding (CSC) improves sparse coding by learning a
shift-invariant dictionary from the data. However, existing CSC algorithms
operate in the batch mode and are expensive, in terms of both space and time,
on large datasets. In this paper, we alleviate these problems by using online
learning. The ke... | 1 | 0 | 0 | 0 | 0 | 0 |
Improving Speech Related Facial Action Unit Recognition by Audiovisual Information Fusion | It is challenging to recognize facial action unit (AU) from spontaneous
facial displays, especially when they are accompanied by speech. The major
reason is that the information is extracted from a single source, i.e., the
visual channel, in the current practice. However, facial activity is highly
correlated with voi... | 1 | 0 | 0 | 0 | 0 | 0 |
Re-purposing Compact Neuronal Circuit Policies to Govern Reinforcement Learning Tasks | We propose an effective method for creating interpretable control agents, by
\textit{re-purposing} the function of a biological neural circuit model, to
govern simulated and real world reinforcement learning (RL) test-beds. Inspired
by the structure of the nervous system of the soil-worm, \emph{C. elegans}, we
introd... | 1 | 0 | 0 | 1 | 0 | 0 |
On the Expected Value of the Determinant of Random Sum of Rank-One Matrices | We present a simple, yet useful result about the expected value of the
determinant of random sum of rank-one matrices. Computing such expectations in
general may involve a sum over exponentially many terms. Nevertheless, we show
that an interesting and useful class of such expectations that arise in, e.g.,
D-optimal ... | 1 | 0 | 1 | 0 | 0 | 0 |
A hyperbolic-equation system approach for magnetized electron fluids in quasi-neutral plasmas | A new approach using a hyperbolic-equation system (HES) is proposed to solve
for the electron fluids in quasi-neutral plasmas. The HES approach avoids
treatments of cross-diffusion terms which cause numerical instabilities in
conventional approaches using an elliptic equation (EE). A test calculation
reveals that the... | 0 | 1 | 0 | 0 | 0 | 0 |
Solving delay differential equations through RBF collocation | A general and easy-to-code numerical method based on radial basis functions
(RBFs) collocation is proposed for the solution of delay differential equations
(DDEs). It relies on the interpolation properties of infinitely smooth RBFs,
which allow for a large accuracy over a scattered and relatively small
discretization... | 0 | 0 | 1 | 0 | 0 | 0 |
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