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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Pitfalls and Best Practices in Algorithm Configuration | Good parameter settings are crucial to achieve high performance in many areas
of artificial intelligence (AI), such as propositional satisfiability solving,
AI planning, scheduling, and machine learning (in particular deep learning).
Automated algorithm configuration methods have recently received much attention
in t... | 1 | 0 | 0 | 0 | 0 | 0 |
Critical behaviors in contagion dynamics | We study the critical behavior of a general contagion model where nodes are
either active (e.g. with opinion A, or functioning) or inactive (e.g. with
opinion B, or damaged). The transitions between these two states are determined
by (i) spontaneous transitions independent of the neighborhood, (ii)
transitions induce... | 0 | 1 | 1 | 0 | 0 | 0 |
Machine Learning in Appearance-based Robot Self-localization | An appearance-based robot self-localization problem is considered in the
machine learning framework. The appearance space is composed of all possible
images, which can be captured by a robot's visual system under all robot
localizations. Using recent manifold learning and deep learning techniques, we
propose a new ge... | 1 | 0 | 0 | 1 | 0 | 0 |
Towards Communication-Aware Robust Topologies | We currently witness the emergence of interesting new network topologies
optimized towards the traffic matrices they serve, such as demand-aware
datacenter interconnects (e.g., ProjecToR) and demand-aware overlay networks
(e.g., SplayNets). This paper introduces a formal framework and approach to
reason about and des... | 1 | 0 | 0 | 0 | 0 | 0 |
Zero-shot Domain Adaptation without Domain Semantic Descriptors | We propose a method to infer domain-specific models such as classifiers for
unseen domains, from which no data are given in the training phase, without
domain semantic descriptors. When training and test distributions are
different, standard supervised learning methods perform poorly. Zero-shot
domain adaptation atte... | 0 | 0 | 0 | 1 | 0 | 0 |
Network modelling of topological domains using Hi-C data | Genome-wide chromosome conformation capture techniques such as Hi-C enable
the generation of 3D genome contact maps and offer new pathways toward
understanding the spatial organization of genome. One specific feature of the
3D organization is known as topologically associating domains (TADs), which are
densely intera... | 0 | 0 | 0 | 1 | 0 | 0 |
On a Possible Giant Impact Origin for the Colorado Plateau | It is proposed and substantiated that an extraterrestrial object of the
approximate size and mass of Planet Mars, impacting the Earth in an oblique
angle along an approximately NE-SW route (with respect to the current
orientation of the North America continent) around 750 million years ago (750
Ma), is likely to be t... | 0 | 1 | 0 | 0 | 0 | 0 |
Reversing Parallel Programs with Blocks and Procedures | We show how to reverse a while language extended with blocks, local
variables, procedures and the interleaving parallel composition. Annotation is
defined along with a set of operational semantics capable of storing necessary
reversal information, and identifiers are introduced to capture the
interleaving order of an... | 1 | 0 | 0 | 0 | 0 | 0 |
Detection of the Stellar Intracluster Medium in Perseus (Abell 426) | Hubble Space Telescope photometry from the ACS/WFC and WFPC2 cameras is used
to detect and measure globular clusters (GCs) in the central region of the rich
Perseus cluster of galaxies. A detectable population of Intragalactic GCs is
found extending out to at least 500 kpc from the cluster center. These objects
displ... | 0 | 1 | 0 | 0 | 0 | 0 |
Binets: fundamental building blocks for phylogenetic networks | Phylogenetic networks are a generalization of evolutionary trees that are
used by biologists to represent the evolution of organisms which have undergone
reticulate evolution. Essentially, a phylogenetic network is a directed acyclic
graph having a unique root in which the leaves are labelled by a given set of
specie... | 1 | 0 | 1 | 0 | 0 | 0 |
G-Deformations of maps into projective space | $G$-deformability of maps into projective space is characterised by the
existence of certain Lie algebra valued 1-forms. This characterisation gives a
unified way to obtain well known results regarding deformability in different
geometries.
| 0 | 0 | 1 | 0 | 0 | 0 |
Cloudless atmospheres for young low-gravity substellar objects | Atmospheric modeling of low-gravity (VL-G) young brown dwarfs remains a
challenge. The presence of very thick clouds has been suggested because of
their extremely red near-infrared (NIR) spectra, but no cloud models provide a
good fit to the data with a radius compatible with evolutionary models for
these objects. We... | 0 | 1 | 0 | 0 | 0 | 0 |
On the State of the Art of Evaluation in Neural Language Models | Ongoing innovations in recurrent neural network architectures have provided a
steady influx of apparently state-of-the-art results on language modelling
benchmarks. However, these have been evaluated using differing code bases and
limited computational resources, which represent uncontrolled sources of
experimental v... | 1 | 0 | 0 | 0 | 0 | 0 |
Weakly Supervised Audio Source Separation via Spectrum Energy Preserved Wasserstein Learning | Separating audio mixtures into individual instrument tracks has been a long
standing challenging task. We introduce a novel weakly supervised audio source
separation approach based on deep adversarial learning. Specifically, our loss
function adopts the Wasserstein distance which directly measures the
distribution di... | 1 | 0 | 0 | 0 | 0 | 0 |
Proof of a conjecture of Kløve on permutation codes under the Chebychev distance | Let $d$ be a positive integer and $x$ a real number. Let $A_{d, x}$ be a
$d\times 2d$ matrix with its entries $$ a_{i,j}=\left\{ \begin{array}{ll} x\ \
& \mbox{for} \ 1\leqslant j\leqslant d+1-i, 1\ \ & \mbox{for} \ d+2-i\leqslant
j\leqslant d+i, 0\ \ & \mbox{for} \ d+1+i\leqslant j\leqslant 2d. \end{array}
\right. $... | 1 | 0 | 0 | 0 | 0 | 0 |
Herschel observations of the Galactic HII region RCW 79 | Triggered star formation around HII regions could be an important process.
The Galactic HII region RCW 79 is a prototypical object for triggered high-mass
star formation. We take advantage of Herschel data from the surveys HOBYS,
"Evolution of Interstellar Dust", and Hi-Gal to extract compact sources in this
region, ... | 0 | 1 | 0 | 0 | 0 | 0 |
Software-Defined Robotics -- Idea & Approach | The methodology of Software-Defined Robotics hierarchical-based and
stand-alone framework can be designed and implemented to program and control
different sets of robots, regardless of their manufacturers' parameters and
specifications, with unified commands and communications. This framework
approach will increase t... | 1 | 0 | 0 | 0 | 0 | 0 |
Stability interchanges in a curved Sitnikov problem | We consider a curved Sitnikov problem, in which an infinitesimal particle
moves on a circle under the gravitational influence of two equal masses in
Keplerian motion within a plane perpendicular to that circle. There are two
equilibrium points, whose stability we are studying. We show that one of the
equilibrium poin... | 0 | 1 | 1 | 0 | 0 | 0 |
Hardy Spaces over Half-strip Domains | We define Hardy spaces $H^p(\Omega_\pm)$ on half-strip domain~$\Omega_+$ and
$\Omega_-= \mathbb{C}\setminus\overline{\Omega_+}$, where $0<p<\infty$, and
prove that functions in $H^p(\Omega_\pm)$ has non-tangential boundary limit
a.e. on $\Gamma$, the common boundary of $\Omega_\pm$. We then prove that
Cauchy integral... | 0 | 0 | 1 | 0 | 0 | 0 |
An Optimization Framework with Flexible Inexact Inner Iterations for Nonconvex and Nonsmooth Programming | In recent years, numerous vision and learning tasks have been (re)formulated
as nonconvex and nonsmooth programmings(NNPs). Although some algorithms have
been proposed for particular problems, designing fast and flexible optimization
schemes with theoretical guarantee is a challenging task for general NNPs. It
has be... | 1 | 0 | 1 | 0 | 0 | 0 |
Attitude and angular velocity tracking for a rigid body using geometric methods on the two-sphere | The control task of tracking a reference pointing direction (the attitude
about the pointing direction is irrelevant) while obtaining a desired angular
velocity (PDAV) around the pointing direction using geometric techniques is
addressed here. Existing geometric controllers developed on the two-sphere only
address th... | 1 | 0 | 1 | 0 | 0 | 0 |
Miscomputation in software: Learning to live with errors | Computer programs do not always work as expected. In fact, ominous warnings
about the desperate state of the software industry continue to be released with
almost ritualistic regularity. In this paper, we look at the 60 years history
of programming and at the different practical methods that software community
develo... | 1 | 0 | 0 | 0 | 0 | 0 |
The Combinatorics of Weighted Vector Compositions | A vector composition of a vector $\mathbf{\ell}$ is a matrix $\mathbf{A}$
whose rows sum to $\mathbf{\ell}$. We define a weighted vector composition as a
vector composition in which the column values of $\mathbf{A}$ may appear in
different colors. We study vector compositions from different viewpoints: (1)
We show ho... | 1 | 0 | 1 | 0 | 0 | 0 |
Fast Linear Model for Knowledge Graph Embeddings | This paper shows that a simple baseline based on a Bag-of-Words (BoW)
representation learns surprisingly good knowledge graph embeddings. By casting
knowledge base completion and question answering as supervised classification
problems, we observe that modeling co-occurences of entities and relations
leads to state-o... | 1 | 0 | 0 | 1 | 0 | 0 |
Deep learning for plasma tomography using the bolometer system at JET | Deep learning is having a profound impact in many fields, especially those
that involve some form of image processing. Deep neural networks excel in
turning an input image into a set of high-level features. On the other hand,
tomography deals with the inverse problem of recreating an image from a number
of projection... | 0 | 1 | 0 | 1 | 0 | 0 |
Assembly Bias and Splashback in Galaxy Clusters | We use publicly available data for the Millennium Simulation to explore the
implications of the recent detection of assembly bias and splashback signatures
in a large sample of galaxy clusters. These were identified in the SDSS/DR8
photometric data by the redMaPPer algorithm and split into high- and
low-concentration... | 0 | 1 | 0 | 0 | 0 | 0 |
Accelerating Kernel Classifiers Through Borders Mapping | Support vector machines (SVM) and other kernel techniques represent a family
of powerful statistical classification methods with high accuracy and broad
applicability. Because they use all or a significant portion of the training
data, however, they can be slow, especially for large problems. Piecewise
linear classif... | 1 | 0 | 0 | 1 | 0 | 0 |
Information Criterion for Minimum Cross-Entropy Model Selection | This paper considers the problem of approximating a density when it can be
evaluated up to a normalizing constant at a finite number of points. This
density approximation problem is ubiquitous in machine learning, such as
approximating a posterior density for Bayesian inference and estimating an
optimal density for i... | 0 | 0 | 0 | 1 | 0 | 0 |
Scaling relations in large-Prandtl-number natural thermal convection | In this study we follow Grossmann and Lohse, Phys. Rev. Lett. 86 (2001), who
derived various scalings regimes for the dependence of the Nusselt number $Nu$
and the Reynolds number $Re$ on the Rayleigh number $Ra$ and the Prandtl number
$Pr$. We focus on theoretical arguments as well as on numerical simulations for
th... | 0 | 1 | 0 | 0 | 0 | 0 |
The renormalization method from continuous to discrete dynamical systems: asymptotic solutions, reductions and invariant manifolds | The renormalization method based on the Taylor expansion for asymptotic
analysis of differential equations is generalized to difference equations. The
proposed renormalization method is based on the Newton-Maclaurin expansion.
Several basic theorems on the renormalization method are proven. Some
interesting applicati... | 0 | 0 | 1 | 0 | 0 | 0 |
A Stress/Displacement Virtual Element Method for Plane Elasticity Problems | The numerical approximation of 2D elasticity problems is considered, in the
framework of the small strain theory and in connection with the mixed
Hellinger-Reissner variational formulation. A low-order Virtual Element Method
(VEM) with a-priori symmetric stresses is proposed. Several numerical tests are
provided, alo... | 0 | 0 | 1 | 0 | 0 | 0 |
Estimation of the lead-lag parameter between two stochastic processes driven by fractional Brownian motions | In this paper, we consider the problem of estimating the lead-lag parameter
between two stochastic processes driven by fractional Brownian motions (fBMs)
of the Hurst parameter greater than 1/2. First we propose a lead-lag model
between two stochastic processes involving fBMs, and then construct a
consistent estimato... | 0 | 0 | 1 | 1 | 0 | 0 |
Multi-resolution polymer Brownian dynamics with hydrodynamic interactions | A polymer model given in terms of beads, interacting through Hookean springs
and hydrodynamic forces, is studied. Brownian dynamics description of this
bead-spring polymer model is extended to multiple resolutions. Using this
multiscale approach, a modeller can efficiently look at different regions of
the polymer in ... | 0 | 1 | 0 | 0 | 0 | 0 |
Learning Theory of Distributed Regression with Bias Corrected Regularization Kernel Network | Distributed learning is an effective way to analyze big data. In distributed
regression, a typical approach is to divide the big data into multiple blocks,
apply a base regression algorithm on each of them, and then simply average the
output functions learnt from these blocks. Since the average process will
decrease ... | 1 | 0 | 0 | 1 | 0 | 0 |
Cluster-based Kriging Approximation Algorithms for Complexity Reduction | Kriging or Gaussian Process Regression is applied in many fields as a
non-linear regression model as well as a surrogate model in the field of
evolutionary computation. However, the computational and space complexity of
Kriging, that is cubic and quadratic in the number of data points respectively,
becomes a major bo... | 1 | 0 | 0 | 1 | 0 | 0 |
How to model fake news | Over the past three years it has become evident that fake news is a danger to
democracy. However, until now there has been no clear understanding of how to
define fake news, much less how to model it. This paper addresses both these
issues. A definition of fake news is given, and two approaches for the
modelling of f... | 1 | 0 | 0 | 0 | 0 | 1 |
Analysis of Dropout in Online Learning | Deep learning is the state-of-the-art in fields such as visual object
recognition and speech recognition. This learning uses a large number of layers
and a huge number of units and connections. Therefore, overfitting is a serious
problem with it, and the dropout which is a kind of regularization tool is
used. However... | 1 | 0 | 0 | 1 | 0 | 0 |
TADPOLE Challenge: Prediction of Longitudinal Evolution in Alzheimer's Disease | The Alzheimer's Disease Prediction Of Longitudinal Evolution (TADPOLE)
Challenge compares the performance of algorithms at predicting future evolution
of individuals at risk of Alzheimer's disease. TADPOLE Challenge participants
train their models and algorithms on historical data from the Alzheimer's
Disease Neuroim... | 0 | 0 | 0 | 1 | 1 | 0 |
A Deep Cascade of Convolutional Neural Networks for MR Image Reconstruction | The acquisition of Magnetic Resonance Imaging (MRI) is inherently slow.
Inspired by recent advances in deep learning, we propose a framework for
reconstructing MR images from undersampled data using a deep cascade of
convolutional neural networks to accelerate the data acquisition process. We
show that for Cartesian ... | 1 | 0 | 0 | 0 | 0 | 0 |
Advances in Joint CTC-Attention based End-to-End Speech Recognition with a Deep CNN Encoder and RNN-LM | We present a state-of-the-art end-to-end Automatic Speech Recognition (ASR)
model. We learn to listen and write characters with a joint Connectionist
Temporal Classification (CTC) and attention-based encoder-decoder network. The
encoder is a deep Convolutional Neural Network (CNN) based on the VGG network.
The CTC ne... | 1 | 0 | 0 | 0 | 0 | 0 |
The Social and Work Structure of an Afterschool Math Club | This study focuses on the social structure and interpersonal dynamics of an
afterschool math club for middle schoolers. Using social network analysis, two
networks were formed and analyzed: The network of friendship relationships and
the network of working relationships. The interconnections and correlations
between ... | 0 | 0 | 1 | 0 | 0 | 0 |
Fourier Transform of Schwartz Algebras on Groups in the Harish-Chandra class | It is well-known that the Harish-Chandra transform, $f\mapsto\mathcal{H}f,$
is a topological isomorphism of the spherical (Schwartz) convolution algebra
$\mathcal{C}^{p}(G//K)$ (where $K$ is a maximal compact subgroup of any
arbitrarily chosen group $G$ in the Harish-Chandra class and $0<p\leq2$) onto
the (Schwartz) ... | 0 | 0 | 1 | 0 | 0 | 0 |
Mutual Information and Optimality of Approximate Message-Passing in Random Linear Estimation | We consider the estimation of a signal from the knowledge of its noisy linear
random Gaussian projections. A few examples where this problem is relevant are
compressed sensing, sparse superposition codes, and code division multiple
access. There has been a number of works considering the mutual information for
this p... | 1 | 1 | 1 | 0 | 0 | 0 |
A Memristor-Based Optimization Framework for AI Applications | Memristors have recently received significant attention as ubiquitous
device-level components for building a novel generation of computing systems.
These devices have many promising features, such as non-volatility, low power
consumption, high density, and excellent scalability. The ability to control
and modify bias... | 1 | 0 | 0 | 1 | 0 | 0 |
Estimating parameters of a directed weighted graph model with beta-distributed edge-weights | We introduce a directed, weighted random graph model, where the edge-weights
are independent and beta-distributed with parameters depending on their
endpoints. We will show that the row- and column-sums of the transformed
edge-weight matrix are sufficient statistics for the parameters, and use the
theory of exponenti... | 0 | 0 | 1 | 1 | 0 | 0 |
On the Performance of Reduced-Complexity Transmit/Receive Diversity Systems over MIMO-V2V Channel Model | In this letter, we investigate the performance of multiple-input
multiple-output techniques in a vehicle-to-vehicle communication system. We
consider both transmit antenna selection with maximal-ratio combining and
transmit antenna selection with selection combining. The channel propagation
model between two vehicles... | 1 | 0 | 0 | 0 | 0 | 0 |
Internal migration and education: A cross-national comparison | Migration the main process shaping patterns of human settlement within and
between countries. It is widely acknowledged to be integral to the process of
human development as it plays a significant role in enhancing educational
outcomes. At regional and national levels, internal migration underpins the
efficient funct... | 0 | 0 | 0 | 0 | 0 | 1 |
Free differential Lie Rota-Baxter algebras and Gröbner-Shirshov bases | We establish the Gröbner-Shirshov bases theory for differential Lie
$\Omega$-algebras. As an application, we give a linear basis of a free
differential Lie Rota-Baxter algebra on a set.
| 0 | 0 | 1 | 0 | 0 | 0 |
Conversion Rate Optimization through Evolutionary Computation | Conversion optimization means designing a web interface so that as many users
as possible take a desired action on it, such as register or purchase. Such
design is usually done by hand, testing one change at a time through A/B
testing, or a limited number of combinations through multivariate testing,
making it possib... | 1 | 0 | 0 | 0 | 0 | 0 |
Emergence of spatial curvature | This paper investigates the phenomenon of emergence of spatial curvature.
This phenomenon is absent in the Standard Cosmological Model, which has a flat
and fixed spatial curvature (small perturbations are considered in the Standard
Cosmological Model but their global average vanishes, leading to spatial
flatness at ... | 0 | 1 | 0 | 0 | 0 | 0 |
Asymptotic generalized bivariate extreme with random index | In many biological, agricultural, military activity problems and in some
quality control problems, it is almost impossible to have a fixed sample size,
because some observations are always lost for various reasons. Therefore, the
sample size itself is considered frequently to be a random variable (rv). The
class of l... | 0 | 0 | 1 | 1 | 0 | 0 |
On problems in the calculus of variations in increasingly elongated domains | We consider minimization problems in the calculus of variations set in a
sequence of domains the size of which tends to infinity in certain directions
and such that the data only depend on the coordinates in the directions that
remain constant. We study the asymptotic behavior of minimizers in various
situations and ... | 0 | 0 | 1 | 0 | 0 | 0 |
Inequalities related to Symmetrized Harmonic Convex Functions | In this paper, we extend the Hermite-Hadamard type $\dot{I}$scan inequality
to the class of symmetrized harmonic convex functions. The corresponding
version for harmonic h-convex functions is also investigated. Furthermore, we
establish Hermite-Hadamard type inequalites for the product of a harmonic
convex function w... | 0 | 0 | 1 | 0 | 0 | 0 |
Parameter estimation for fractional Ornstein-Uhlenbeck processes of general Hurst parameter | This paper provides several statistical estimators for the drift and
volatility parameters of an Ornstein-Uhlenbeck process driven by fractional
Brownian motion, whose observations can be made either continuously or at
discrete time instants. First and higher order power variations are used to
estimate the volatility... | 0 | 0 | 1 | 1 | 0 | 0 |
E-polynomials of $PGL(2,\mathbb{C})$-character varieties of surface groups | In this paper, we compute the E-polynomials of the
$PGL(2,\mathbb{C})$-character varieties associated to surfaces of genus $g$
with one puncture, for any holonomy around it, and compare it with its
Langlands dual case, $SL(2,\mathbb{C})$. The study is based on the
stratification of the space of representations and on... | 0 | 0 | 1 | 0 | 0 | 0 |
Security Analysis of Cache Replacement Policies | Modern computer architectures share physical resources between different
programs in order to increase area-, energy-, and cost-efficiency.
Unfortunately, sharing often gives rise to side channels that can be exploited
for extracting or transmitting sensitive information. We currently lack
techniques for systematic r... | 1 | 0 | 0 | 0 | 0 | 0 |
Supercongruences related to ${}_3F_2(1)$ involving harmonic numbers | We show various supercongruences for truncated series which involve central
binomial coefficients and harmonic numbers. The corresponding infinite series
are also evaluated.
| 0 | 0 | 1 | 0 | 0 | 0 |
Dynamic Layer Normalization for Adaptive Neural Acoustic Modeling in Speech Recognition | Layer normalization is a recently introduced technique for normalizing the
activities of neurons in deep neural networks to improve the training speed and
stability. In this paper, we introduce a new layer normalization technique
called Dynamic Layer Normalization (DLN) for adaptive neural acoustic modeling
in speech... | 1 | 0 | 0 | 0 | 0 | 0 |
First-Order vs. Second-Order Encodings for LTLf-to-Automata Translation | Translating formulas of Linear Temporal Logic (LTL) over finite traces, or
LTLf, to symbolic Deterministic Finite Automata (DFA) plays an important role
not only in LTLf synthesis, but also in synthesis for Safety LTL formulas. The
translation is enabled by using MONA, a powerful tool for symbolic, BDD-based,
DFA con... | 1 | 0 | 0 | 0 | 0 | 0 |
Regularity results and parametrices of semi-linear boundary problems of product type | This short note describes the benefit one obtains from a specific
construction of a family of parametrices for a class of elliptic boundary value
problems perturbed by non-linear terms of product type. The construction is
based on the Boutet de Monvel calculus of pseudo-differential boundary
operators for the linear ... | 0 | 0 | 1 | 0 | 0 | 0 |
$\left( β, \varpi \right)$-stability for cross-validation and the choice of the number of folds | In this paper, we introduce a new concept of stability for cross-validation,
called the $\left( \beta, \varpi \right)$-stability, and use it as a new
perspective to build the general theory for cross-validation. The $\left(
\beta, \varpi \right)$-stability mathematically connects the generalization
ability and the st... | 1 | 0 | 1 | 1 | 0 | 0 |
Directional convexity of harmonic mappings | The convolution properties are discussed for the complex-valued harmonic
functions in the unit disk $\mathbb{D}$ constructed from the harmonic shearing
of the analytic function $\phi(z):=\int_0^z
(1/(1-2\xi\textit{e}^{\textit{i}\mu}\cos\nu+\xi^2\textit{e}^{2\textit{i}\mu}))\textit{d}\xi$,
where $\mu$ and $\nu$ are re... | 0 | 0 | 1 | 0 | 0 | 0 |
Optimal Non-uniform Deployments in Ultra-Dense Finite-Area Cellular Networks | Network densification and heterogenisation through the deployment of small
cellular access points (picocells and femtocells) are seen as key mechanisms in
handling the exponential increase in cellular data traffic. Modelling such
networks by leveraging tools from Stochastic Geometry has proven particularly
useful in ... | 1 | 0 | 0 | 0 | 0 | 0 |
Plan, Attend, Generate: Character-level Neural Machine Translation with Planning in the Decoder | We investigate the integration of a planning mechanism into an
encoder-decoder architecture with an explicit alignment for character-level
machine translation. We develop a model that plans ahead when it computes
alignments between the source and target sequences, constructing a matrix of
proposed future alignments a... | 1 | 0 | 0 | 0 | 0 | 0 |
Deep Recurrent NMF for Speech Separation by Unfolding Iterative Thresholding | In this paper, we propose a novel recurrent neural network architecture for
speech separation. This architecture is constructed by unfolding the iterations
of a sequential iterative soft-thresholding algorithm (ISTA) that solves the
optimization problem for sparse nonnegative matrix factorization (NMF) of
spectrogram... | 1 | 0 | 0 | 1 | 0 | 0 |
Birth of isolated nested cylinders and limit cycles in 3D piecewise smooth vector fields with symmetry | Our start point is a 3D piecewise smooth vector field defined in two zones
and presenting a shared fold curve for the two smooth vector fields considered.
Moreover, these smooth vector fields are symmetric relative to the fold curve,
giving raise to a continuum of nested topological cylinders such that each
orthogona... | 0 | 0 | 1 | 0 | 0 | 0 |
The difficulty of folding self-folding origami | Why is it difficult to refold a previously folded sheet of paper? We show
that even crease patterns with only one designed folding motion inevitably
contain an exponential number of `distractor' folding branches accessible from
a bifurcation at the flat state. Consequently, refolding a sheet requires
finding the grou... | 0 | 1 | 0 | 0 | 0 | 0 |
Integrable Trotterization: Local Conservation Laws and Boundary Driving | We discuss a general procedure to construct an integrable real-time
trotterization of interacting lattice models. As an illustrative example we
consider a spin-$1/2$ chain, with continuous time dynamics described by the
isotropic ($XXX$) Heisenberg Hamiltonian. For periodic boundary conditions
local conservation laws... | 0 | 1 | 0 | 0 | 0 | 0 |
The Multivariate Hawkes Process in High Dimensions: Beyond Mutual Excitation | The Hawkes process is a class of point processes whose future depends on its
own history. Previous theoretical work on the Hawkes process is limited to the
case of a mutually-exciting process, in which a past event can only increase
the occurrence of future events. However, in neuronal networks and other
real-world a... | 0 | 0 | 0 | 1 | 0 | 0 |
Aerial-Ground collaborative sensing: Third-Person view for teleoperation | Rapid deployment and operation are key requirements in time critical
application, such as Search and Rescue (SaR). Efficiently teleoperated ground
robots can support first-responders in such situations. However, first-person
view teleoperation is sub-optimal in difficult terrains, while a third-person
perspective can... | 1 | 0 | 0 | 0 | 0 | 0 |
A universal thin film model for Ginzburg-Landau energy with dipolar interaction | We present an analytical treatment of a three-dimensional variational model
of a system that exhibits a second-order phase transition in the presence of
dipolar interactions. Within the framework of Ginzburg-Landau theory, we
concentrate on the case in which the domain occupied by the sample has the
shape of a flat t... | 0 | 1 | 1 | 0 | 0 | 0 |
LOCATA challenge: speaker localization with a planar array | This document describes our submission to the 2018 LOCalization And TrAcking
(LOCATA) challenge (Tasks 1, 3, 5). We estimate the 3D position of a speaker
using the Global Coherence Field (GCF) computed from multiple microphone pairs
of a DICIT planar array. One of the main challenges when using such an array
with omn... | 1 | 0 | 0 | 0 | 0 | 0 |
Less Is More: A Comprehensive Framework for the Number of Components of Ensemble Classifiers | The number of component classifiers chosen for an ensemble greatly impacts
the prediction ability. In this paper, we use a geometric framework for a
priori determining the ensemble size, which is applicable to most of existing
batch and online ensemble classifiers. There are only a limited number of
studies on the en... | 1 | 0 | 0 | 1 | 0 | 0 |
Large-Scale Low-Rank Matrix Learning with Nonconvex Regularizers | Low-rank modeling has many important applications in computer vision and
machine learning. While the matrix rank is often approximated by the convex
nuclear norm, the use of nonconvex low-rank regularizers has demonstrated
better empirical performance. However, the resulting optimization problem is
much more challeng... | 1 | 0 | 0 | 1 | 0 | 0 |
Computational Eco-Systems for Handwritten Digits Recognition | Inspired by the importance of diversity in biological system, we built an
heterogeneous system that could achieve this goal. Our architecture could be
summarized in two basic steps. First, we generate a diverse set of
classification hypothesis using both Convolutional Neural Networks, currently
the state-of-the-art t... | 0 | 0 | 0 | 1 | 0 | 0 |
Compressing networks with super nodes | Community detection is a commonly used technique for identifying groups in a
network based on similarities in connectivity patterns. To facilitate community
detection in large networks, we recast the network to be partitioned into a
smaller network of 'super nodes', each super node comprising one or more nodes
in the... | 1 | 1 | 0 | 0 | 0 | 0 |
Mode specific electronic friction in dissociative chemisorption on metal surfaces: H$_2$ on Ag(111) | Electronic friction and the ensuing nonadiabatic energy loss play an
important role in chemical reaction dynamics at metal surfaces. Using molecular
dynamics with electronic friction evaluated on-the-fly from Density Functional
Theory, we find strong mode dependence and a dominance of nonadiabatic energy
loss along t... | 0 | 1 | 0 | 0 | 0 | 0 |
The quantum auxiliary linear problem & quantum Darboux-Backlund transformations | We explore the notion of the quantum auxiliary linear problem and the
associated problem of quantum Backlund transformations (BT). In this context we
systematically construct the analogue of the classical formula that provides
the whole hierarchy of the time components of Lax pairs at the quantum level
for both close... | 0 | 1 | 0 | 0 | 0 | 0 |
Simplified Minimal Gated Unit Variations for Recurrent Neural Networks | Recurrent neural networks with various types of hidden units have been used
to solve a diverse range of problems involving sequence data. Two of the most
recent proposals, gated recurrent units (GRU) and minimal gated units (MGU),
have shown comparable promising results on example public datasets. In this
paper, we i... | 1 | 0 | 0 | 1 | 0 | 0 |
Parallel G-duplex and C-duplex DNA with Uninterrupted Spines of AgI-Mediated Base Pairs | Hydrogen bonding between nucleobases produces diverse DNA structural motifs,
including canonical duplexes, guanine (G) quadruplexes and cytosine (C)
i-motifs. Incorporating metal-mediated base pairs into nucleic acid structures
can introduce new functionalities and enhanced stabilities. Here we
demonstrate, using mas... | 0 | 0 | 0 | 0 | 1 | 0 |
Constraints on Vacuum Energy from Structure Formation and Nucleosynthesis | This paper derives an upper limit on the density $\rho_{\scriptstyle\Lambda}$
of dark energy based on the requirement that cosmological structure forms
before being frozen out by the eventual acceleration of the universe. By
allowing for variations in both the cosmological parameters and the strength of
gravity, the ... | 0 | 1 | 0 | 0 | 0 | 0 |
Dynamic Mobile Edge Caching with Location Differentiation | Mobile edge caching enables content delivery directly within the radio access
network, which effectively alleviates the backhaul burden and reduces
round-trip latency. To fully exploit the edge resources, the most popular
contents should be identified and cached. Observing that content popularity
varies greatly at di... | 1 | 0 | 0 | 0 | 0 | 0 |
Online Learning for Distribution-Free Prediction | We develop an online learning method for prediction, which is important in
problems with large and/or streaming data sets. We formulate the learning
approach using a covariance-fitting methodology, and show that the resulting
predictor has desirable computational and distribution-free properties: It is
implemented on... | 1 | 0 | 0 | 1 | 0 | 0 |
Thermal transitions, pseudogap behavior and BCS-BEC crossover in Fermi-Fermi mixtures | We study the mass imbalanced Fermi-Fermi mixture within the framework of a
two-dimensional lattice fermion model. Based on the thermodynamic and species
dependent quasiparticle behavior we map out the finite temperature phase
diagram of this system and show that unlike the balanced Fermi superfluid there
are now two ... | 0 | 1 | 0 | 0 | 0 | 0 |
Spectral Approximation for Ergodic CMV Operators with an Application to Quantum Walks | We establish concrete criteria for fully supported absolutely continuous
spectrum for ergodic CMV matrices and purely absolutely continuous spectrum for
limit-periodic CMV matrices. We proceed by proving several variational
estimates on the measure of the spectrum and the vanishing set of the Lyapunov
exponent for CM... | 0 | 0 | 1 | 0 | 0 | 0 |
Quantitative Photoacoustic Imaging in the Acoustic Regime using SPIM | While in standard photoacoustic imaging the propagation of sound waves is
modeled by the standard wave equation, our approach is based on a generalized
wave equation with variable sound speed and material density, respectively. In
this paper we present an approach for photoacoustic imaging, which in addition
to recov... | 0 | 0 | 1 | 0 | 0 | 0 |
Integrated Deep and Shallow Networks for Salient Object Detection | Deep convolutional neural network (CNN) based salient object detection
methods have achieved state-of-the-art performance and outperform those
unsupervised methods with a wide margin. In this paper, we propose to integrate
deep and unsupervised saliency for salient object detection under a unified
framework. Specific... | 1 | 0 | 0 | 0 | 0 | 0 |
Feedback Capacity over Networks | In this paper, we investigate the fundamental limitations of feedback
mechanism in dealing with uncertainties for network systems. The study of
maximum capability of feedback control was pioneered in Xie and Guo (2000) for
scalar systems with nonparametric nonlinear uncertainty. In a network setting,
nodes with unkno... | 1 | 0 | 0 | 0 | 0 | 0 |
Flexural phonons in supported graphene: from pinning to localization | We identify graphene layer on a disordered substrate as a possible system
where Anderson localization of phonons can be observed. Generally, observation
of localization for scattering waves is not simple, because the Rayleigh
scattering is inversely proportional to a high power of wavelength. The
situation is radical... | 0 | 1 | 0 | 0 | 0 | 0 |
Test them all, is it worth it? Assessing configuration sampling on the JHipster Web development stack | Many approaches for testing configurable software systems start from the same
assumption: it is impossible to test all configurations. This motivated the
definition of variability-aware abstractions and sampling techniques to cope
with large configuration spaces. Yet, there is no theoretical barrier that
prevents the... | 1 | 0 | 0 | 0 | 0 | 0 |
Q-Learning Algorithm for VoLTE Closed-Loop Power Control in Indoor Small Cells | We propose a reinforcement learning (RL) based closed loop power control
algorithm for the downlink of the voice over LTE (VoLTE) radio bearer for an
indoor environment served by small cells. The main contributions of our paper
are to 1) use RL to solve performance tuning problems in an indoor cellular
network for vo... | 1 | 0 | 0 | 1 | 0 | 0 |
Ancient shrinking spherical interfaces in the Allen-Cahn flow | We consider the parabolic Allen-Cahn equation in $\mathbb{R}^n$, $n\ge 2$,
$$u_t= \Delta u + (1-u^2)u \quad \hbox{ in } \mathbb{R}^n \times (-\infty,
0].$$ We construct an ancient radially symmetric solution $u(x,t)$ with any
given number $k$ of transition layers between $-1$ and $+1$. At main order they
consist of $... | 0 | 0 | 1 | 0 | 0 | 0 |
Measuring the Eccentricity of Items | The long-tail phenomenon tells us that there are many items in the tail.
However, not all tail items are the same. Each item acquires different kinds of
users. Some items are loved by the general public, while some items are
consumed by eccentric fans. In this paper, we propose a novel metric, item
eccentricity, to i... | 1 | 0 | 0 | 0 | 0 | 0 |
Dataset: Rare Event Classification in Multivariate Time Series | A real-world dataset is provided from a pulp-and-paper manufacturing
industry. The dataset comes from a multivariate time series process. The data
contains a rare event of paper break that commonly occurs in the industry. The
data contains sensor readings at regular time-intervals (x's) and the event
label (y). The p... | 0 | 0 | 0 | 1 | 0 | 0 |
Experimental verification of stopping-power prediction from single- and dual-energy computed tomography in biological tissues | An experimental setup for consecutive measurement of ion and x-ray absorption
in tissue or other materials is introduced. With this setup using a 3D-printed
sample container, the reference stopping-power ratio (SPR) of materials can be
measured with an uncertainty of below 0.1%. A total of 65 porcine and bovine
tissu... | 0 | 1 | 0 | 0 | 0 | 0 |
How to Beat Science and Influence People: Policy Makers and Propaganda in Epistemic Networks | In their recent book Merchants of Doubt [New York:Bloomsbury 2010], Naomi
Oreskes and Erik Conway describe the "tobacco strategy", which was used by the
tobacco industry to influence policy makers regarding the health risks of
tobacco products. The strategy involved two parts, consisting of (1) promoting
and sharing ... | 1 | 0 | 0 | 0 | 0 | 0 |
A complete and partial integrability technique of the Lorenz system | In this paper we deal with the well-known nonlinear Lorenz system that
describes the deterministic chaos phenomenon. We consider an interesting
problem with time-varying phenomena in quantum optics. Then we establish from
the motion equations the passage to the Lorenz system. Furthermore, we show
that the reduction t... | 0 | 1 | 0 | 0 | 0 | 0 |
Comparision of the definitions of generalized solution of the Cauchy problem for quasi-linear equation | In preprint we consider and compare different definitions of generalized
solution of the Cauchy problem for 1d-scalar quasilinear equation (conservation
law). We start from the classical approaches goes back to I.M. Gelfand, O.A.
Oleinik, S.N. Kruzhkov and move to the modern finite-difference approximations
approache... | 0 | 0 | 1 | 0 | 0 | 0 |
On The Complexity of Sparse Label Propagation | This paper investigates the computational complexity of sparse label
propagation which has been proposed recently for processing network structured
data. Sparse label propagation amounts to a convex optimization problem and
might be considered as an extension of basis pursuit from sparse vectors to
network structured... | 0 | 0 | 0 | 1 | 0 | 0 |
Detecting Qualia in Natural and Artificial Agents | The Hard Problem of consciousness has been dismissed as an illusion. By
showing that computers are capable of experiencing, we show that they are at
least rudimentarily conscious with potential to eventually reach
superconsciousness. The main contribution of the paper is a test for confirming
certain subjective exper... | 1 | 0 | 0 | 0 | 0 | 0 |
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