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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Deep-HiTS: Rotation Invariant Convolutional Neural Network for Transient Detection | We introduce Deep-HiTS, a rotation invariant convolutional neural network
(CNN) model for classifying images of transients candidates into artifacts or
real sources for the High cadence Transient Survey (HiTS). CNNs have the
advantage of learning the features automatically from the data while achieving
high performan... | 1 | 1 | 0 | 0 | 0 | 0 |
On Measuring and Quantifying Performance: Error Rates, Surrogate Loss, and an Example in SSL | In various approaches to learning, notably in domain adaptation, active
learning, learning under covariate shift, semi-supervised learning, learning
with concept drift, and the like, one often wants to compare a baseline
classifier to one or more advanced (or at least different) strategies. In this
chapter, we basica... | 1 | 0 | 0 | 1 | 0 | 0 |
Do Reichenbachian Common Cause Systems of Arbitrary Finite Size Exist? | The principle of common cause asserts that positive correlations between
causally unrelated events ought to be explained through the action of some
shared causal factors. Reichenbachian common cause systems are probabilistic
structures aimed at accounting for cases where correlations of the aforesaid
sort cannot be e... | 1 | 1 | 0 | 1 | 0 | 0 |
Co-evolution of nodes and links: diversity driven coexistence in cyclic competition of three species | When three species compete cyclically in a well-mixed, stochastic system of
$N$ individuals, extinction is known to typically occur at times scaling as the
system size $N$. This happens, for example, in rock-paper-scissors games or
conserved Lotka-Volterra models in which every pair of individuals can interact
on a c... | 0 | 0 | 0 | 0 | 1 | 0 |
Online Learning with an Almost Perfect Expert | We study the multiclass online learning problem where a forecaster makes a
sequence of predictions using the advice of $n$ experts. Our main contribution
is to analyze the regime where the best expert makes at most $b$ mistakes and
to show that when $b = o(\log_4{n})$, the expected number of mistakes made by
the opti... | 0 | 0 | 0 | 1 | 0 | 0 |
Actively Learning what makes a Discrete Sequence Valid | Deep learning techniques have been hugely successful for traditional
supervised and unsupervised machine learning problems. In large part, these
techniques solve continuous optimization problems. Recently however, discrete
generative deep learning models have been successfully used to efficiently
search high-dimensio... | 1 | 0 | 0 | 1 | 0 | 0 |
Symmetries and conservation laws of Hamiltonian systems | In this paper we study the infinitesimal symmetries, Newtonoid vector fields,
infinitesimal Noether symmetries and conservation laws of Hamiltonian systems.
Using the dynamical covariant derivative and Jacobi endomorphism on the
cotangent bundle we find the invariant equations of infinitesimal symmetries
and Newtonoi... | 0 | 0 | 1 | 0 | 0 | 0 |
Fractional differential and fractional integral modified-Bloch equations for PFG anomalous diffusion and their general solutions | The studying of anomalous diffusion by pulsed field gradient (PFG) diffusion
technique still faces challenges. Two different research groups have proposed
modified Bloch equation for anomalous diffusion. However, these equations have
different forms and, therefore, yield inconsistent results. The discrepancy in
these... | 0 | 1 | 0 | 0 | 0 | 0 |
Change of the vortex core structure in two-band superconductors at impurity-scattering-driven $s_\pm/s_{++}$ crossover | We report a nontrivial transition in the core structure of vortices in
two-band superconductors as a function of interband impurity scattering. We
demonstrate that, in addition to singular zeros of the order parameter, the
vortices there can acquire a circular nodal line around the singular point in
one of the superc... | 0 | 1 | 0 | 0 | 0 | 0 |
Nearly Optimal Adaptive Procedure with Change Detection for Piecewise-Stationary Bandit | Multi-armed bandit (MAB) is a class of online learning problems where a
learning agent aims to maximize its expected cumulative reward while repeatedly
selecting to pull arms with unknown reward distributions. We consider a
scenario where the reward distributions may change in a piecewise-stationary
fashion at unknow... | 0 | 0 | 0 | 1 | 0 | 0 |
An initial-boundary value problem of the general three-component nonlinear Schrodinger equation with a 4x4 Lax pair on a finite interval | We investigate the initial-boundary value problem for the general
three-component nonlinear Schrodinger (gtc-NLS) equation with a 4x4 Lax pair on
a finite interval by extending the Fokas unified approach. The solutions of the
gtc-NLS equation can be expressed in terms of the solutions of a 4x4 matrix
Riemann-Hilbert ... | 0 | 1 | 1 | 0 | 0 | 0 |
Deep Learning Microscopy | We demonstrate that a deep neural network can significantly improve optical
microscopy, enhancing its spatial resolution over a large field-of-view and
depth-of-field. After its training, the only input to this network is an image
acquired using a regular optical microscope, without any changes to its design.
We blin... | 1 | 1 | 0 | 0 | 0 | 0 |
Effects of pressure impulse and peak pressure of a shock wave on microjet velocity and the onset of cavitation in a microchannel | The development of needle-free injection systems utilizing high-speed
microjets is of great importance to world healthcare. It is thus crucial to
control the microjets, which are often induced by underwater shock waves. In
this contribution from fluid-mechanics point of view, we experimentally
investigate the effect ... | 0 | 1 | 0 | 0 | 0 | 0 |
Clustering with Noisy Queries | In this paper, we initiate a rigorous theoretical study of clustering with
noisy queries (or a faulty oracle). Given a set of $n$ elements, our goal is to
recover the true clustering by asking minimum number of pairwise queries to an
oracle. Oracle can answer queries of the form : "do elements $u$ and $v$ belong
to t... | 1 | 0 | 0 | 1 | 0 | 0 |
Divide-and-Conquer Checkpointing for Arbitrary Programs with No User Annotation | Classical reverse-mode automatic differentiation (AD) imposes only a small
constant-factor overhead in operation count over the original computation, but
has storage requirements that grow, in the worst case, in proportion to the
time consumed by the original computation. This storage blowup can be
ameliorated by che... | 1 | 0 | 0 | 0 | 0 | 0 |
Bow Ties in the Sky II: Searching for Gamma-ray Halos in the Fermi Sky Using Anisotropy | Many-degree-scale gamma-ray halos are expected to surround extragalactic
high-energy gamma ray sources. These arise from the inverse Compton emission of
an intergalactic population of relativistic electron/positron pairs generated
by the annihilation of >100 GeV gamma rays on the extragalactic background
light. These... | 0 | 1 | 0 | 0 | 0 | 0 |
Gain-loss-driven travelling waves in PT-symmetric nonlinear metamaterials | In this work we investigate a one-dimensional parity-time (PT)-symmetric
magnetic metamaterial consisting of split-ring dimers having gain or loss.
Employing a Melnikov analysis we study the existence of localized travelling
waves, i.e. homoclinic or heteroclinic solutions. We find conditions under
which the homoclin... | 0 | 1 | 0 | 0 | 0 | 0 |
CapsuleGAN: Generative Adversarial Capsule Network | We present Generative Adversarial Capsule Network (CapsuleGAN), a framework
that uses capsule networks (CapsNets) instead of the standard convolutional
neural networks (CNNs) as discriminators within the generative adversarial
network (GAN) setting, while modeling image data. We provide guidelines for
designing CapsN... | 0 | 0 | 0 | 1 | 0 | 0 |
sourceR: Classification and Source Attribution of Infectious Agents among Heterogeneous Populations | Zoonotic diseases are a major cause of morbidity, and productivity losses in
both humans and animal populations. Identifying the source of food-borne
zoonoses (e.g. an animal reservoir or food product) is crucial for the
identification and prioritisation of food safety interventions. For many
zoonotic diseases it is ... | 0 | 0 | 0 | 1 | 0 | 0 |
Low resistive edge contacts to CVD-grown graphene using a CMOS compatible metal | The exploitation of the excellent intrinsic electronic properties of graphene
for device applications is hampered by a large contact resistance between the
metal and graphene. The formation of edge contacts rather than top contacts is
one of the most promising solutions for realizing low ohmic contacts. In this
paper... | 0 | 1 | 0 | 0 | 0 | 0 |
Uniqueness of planar vortex patch in incompressible steady flow | We investigate a steady planar flow of an ideal fluid in a bounded simple
connected domain and focus on the vortex patch problem with prescribed
vorticity strength. There are two methods to deal with the existence of
solutions for this problem: the vorticity method and the stream function
method. A long standing open... | 0 | 0 | 1 | 0 | 0 | 0 |
An Equivalence of Fully Connected Layer and Convolutional Layer | This article demonstrates that convolutional operation can be converted to
matrix multiplication, which has the same calculation way with fully connected
layer. The article is helpful for the beginners of the neural network to
understand how fully connected layer and the convolutional layer work in the
backend. To be... | 1 | 0 | 0 | 1 | 0 | 0 |
Critical Points of Neural Networks: Analytical Forms and Landscape Properties | Due to the success of deep learning to solving a variety of challenging
machine learning tasks, there is a rising interest in understanding loss
functions for training neural networks from a theoretical aspect. Particularly,
the properties of critical points and the landscape around them are of
importance to determin... | 1 | 0 | 0 | 1 | 0 | 0 |
When the Annihilator Graph of a Commutative Ring Is Planar or Toroidal? | Let $R$ be a commutative ring with identity, and let $Z(R)$ be the set of
zero-divisors of $R$. The annihilator graph of $R$ is defined as the undirected
graph $AG(R)$ with the vertex set $Z(R)^*=Z(R)\setminus\{0\}$, and two distinct
vertices $x$ and $y$ are adjacent if and only if $ann_R(xy)\neq ann_R(x)\cup
ann_R(y... | 0 | 0 | 1 | 0 | 0 | 0 |
Econometric modelling and forecasting of intraday electricity prices | In the following paper we analyse the ID$_3$-Price on German Intraday
Continuous Electricity Market using an econometric time series model. A
multivariate approach is conducted for hourly and quarter-hourly products
separately. We estimate the model using lasso and elastic net techniques and
perform an out-of-sample ... | 0 | 0 | 0 | 0 | 0 | 1 |
Matrix-Based Characterization of the Motion and Wrench Uncertainties in Robotic Manipulators | Characterization of the uncertainty in robotic manipulators is the focus of
this paper. Based on the random matrix theory (RMT), we propose uncertainty
characterization schemes in which the uncertainty is modeled at the macro
(system) level. This is different from the traditional approaches that model
the uncertainty... | 1 | 0 | 0 | 1 | 0 | 0 |
Good Similar Patches for Image Denoising | Patch-based denoising algorithms like BM3D have achieved outstanding
performance. An important idea for the success of these methods is to exploit
the recurrence of similar patches in an input image to estimate the underlying
image structures. However, in these algorithms, the similar patches used for
denoising are o... | 1 | 0 | 0 | 0 | 0 | 0 |
Ginzburg - Landau expansion in strongly disordered attractive Anderson - Hubbard model | We have studied disordering effects on the coefficients of Ginzburg - Landau
expansion in powers of superconducting order - parameter in attractive Anderson
- Hubbard model within the generalized $DMFT+\Sigma$ approximation. We consider
the wide region of attractive potentials $U$ from the weak coupling region,
where... | 0 | 1 | 0 | 0 | 0 | 0 |
Reallocating and Resampling: A Comparison for Inference | Simulation-based inference plays a major role in modern statistics, and often
employs either reallocating (as in a randomization test) or resampling (as in
bootstrapping). Reallocating mimics random allocation to treatment groups,
while resampling mimics random sampling from a larger population; does it
matter whethe... | 0 | 0 | 1 | 1 | 0 | 0 |
An Efficient Algorithm for Bayesian Nearest Neighbours | K-Nearest Neighbours (k-NN) is a popular classification and regression
algorithm, yet one of its main limitations is the difficulty in choosing the
number of neighbours. We present a Bayesian algorithm to compute the posterior
probability distribution for k given a target point within a data-set,
efficiently and with... | 1 | 0 | 0 | 1 | 0 | 0 |
In search of a new economic model determined by logistic growth | In this paper we extend the work by Ryuzo Sato devoted to the development of
economic growth models within the framework of the Lie group theory. We propose
a new growth model based on the assumption of logistic growth in factors. It is
employed to derive new production functions and introduce a new notion of wage
sh... | 0 | 0 | 1 | 0 | 0 | 0 |
Limits on light WIMPs with a 1 kg-scale germanium detector at 160 eVee physics threshold at the China Jinping Underground Laboratory | We report results of a search for light weakly interacting massive particle
(WIMP) dark matter from the CDEX-1 experiment at the China Jinping Underground
Laboratory (CJPL). Constraints on WIMP-nucleon spin-independent (SI) and
spin-dependent (SD) couplings are derived with a physics threshold of 160 eVee,
from an ex... | 0 | 1 | 0 | 0 | 0 | 0 |
A stellar census of the nearby, young 32 Orionis group | The 32 Orionis group was discovered almost a decade ago and despite the fact
that it represents the first northern, young (age ~ 25 Myr) stellar aggregate
within 100 pc of the Sun ($d \simeq 93$ pc), a comprehensive survey for members
and detailed characterisation of the group has yet to be performed. We present
the ... | 0 | 1 | 0 | 0 | 0 | 0 |
A High-Level Rule-based Language for Software Defined Network Programming based on OpenFlow | This paper proposes XML-Defined Network policies (XDNP), a new high-level
language based on XML notation, to describe network control rules in Software
Defined Network environments. We rely on existing OpenFlow controllers
specifically Floodlight but the novelty of this project is to separate
complicated language- an... | 1 | 0 | 0 | 0 | 0 | 0 |
Domain Objects and Microservices for Systems Development: a roadmap | This paper discusses a roadmap to investigate Domain Objects being an
adequate formalism to capture the peculiarity of microservice architecture, and
to support Software development since the early stages. It provides a survey of
both Microservices and Domain Objects, and it discusses plans and reflections
on how to ... | 1 | 0 | 0 | 0 | 0 | 0 |
Stabilization of prethermal Floquet steady states in a periodically driven dissipative Bose-Hubbard model | We discuss the effect of dissipation on heating which occurs in periodically
driven quantum many body systems. We especially focus on a periodically driven
Bose-Hubbard model coupled to an energy and particle reservoir. Without
dissipation, this model is known to undergo parametric instabilities which can
be consider... | 0 | 1 | 0 | 0 | 0 | 0 |
Compressed Sensing using Generative Models | The goal of compressed sensing is to estimate a vector from an
underdetermined system of noisy linear measurements, by making use of prior
knowledge on the structure of vectors in the relevant domain. For almost all
results in this literature, the structure is represented by sparsity in a
well-chosen basis. We show h... | 1 | 0 | 0 | 1 | 0 | 0 |
Two-part models with stochastic processes for modelling longitudinal semicontinuous data: computationally efficient inference and modelling the overall marginal mean | Several researchers have described two-part models with patient-specific
stochastic processes for analysing longitudinal semicontinuous data. In theory,
such models can offer greater flexibility than the standard two-part model with
patient-specific random effects. However, in practice the high dimensional
integratio... | 0 | 0 | 0 | 1 | 0 | 0 |
Progressive Image Deraining Networks: A Better and Simpler Baseline | Along with the deraining performance improvement of deep networks, their
structures and learning become more and more complicated and diverse, making it
difficult to analyze the contribution of various network modules when
developing new deraining networks. To handle this issue, this paper provides a
better and simpl... | 1 | 0 | 0 | 0 | 0 | 0 |
Optimal Nonparametric Inference under Quantization | Statistical inference based on lossy or incomplete samples is of fundamental
importance in research areas such as signal/image processing, medical image
storage, remote sensing, signal transmission. In this paper, we propose a
nonparametric testing procedure based on quantized samples. In contrast to the
classic nonp... | 1 | 0 | 1 | 1 | 0 | 0 |
Nearest neighbor imputation for general parameter estimation in survey sampling | Nearest neighbor imputation is popular for handling item nonresponse in
survey sampling. In this article, we study the asymptotic properties of the
nearest neighbor imputation estimator for general population parameters,
including population means, proportions and quantiles. For variance estimation,
the conventional ... | 0 | 0 | 0 | 1 | 0 | 0 |
Time-delay signature suppression in a chaotic semiconductor laser by fiber random grating induced distributed feedback | We demonstrate that a semiconductor laser perturbed by the distributed
feedback from a fiber random grating can emit light chaotically without the
time delay signature. A theoretical model is developed based on the
Lang-Kobayashi model in order to numerically explore the chaotic dynamics of
the laser diode subjected ... | 0 | 1 | 0 | 0 | 0 | 0 |
SAFS: A Deep Feature Selection Approach for Precision Medicine | In this paper, we propose a new deep feature selection method based on deep
architecture. Our method uses stacked auto-encoders for feature representation
in higher-level abstraction. We developed and applied a novel feature learning
approach to a specific precision medicine problem, which focuses on assessing
and pr... | 1 | 0 | 0 | 1 | 0 | 0 |
Deep Reasoning with Multi-scale Context for Salient Object Detection | To detect and segment salient objects accurately, existing methods are
usually devoted to designing complex network architectures to fuse powerful
features from the backbone networks. However, they put much less efforts on the
saliency inference module and only use a few fully convolutional layers to
perform saliency... | 1 | 0 | 0 | 0 | 0 | 0 |
On Estimation of $L_{r}$-Norms in Gaussian White Noise Models | We provide a complete picture of asymptotically minimax estimation of
$L_r$-norms (for any $r\ge 1$) of the mean in Gaussian white noise model over
Nikolskii-Besov spaces. In this regard, we complement the work of Lepski,
Nemirovski and Spokoiny (1999), who considered the cases of $r=1$ (with
poly-logarithmic gap bet... | 1 | 0 | 1 | 1 | 0 | 0 |
Secure communications with cooperative jamming: Optimal power allocation and secrecy outage analysis | This paper studies the secrecy rate maximization problem of a secure wireless
communication system, in the presence of multiple eavesdroppers. The security
of the communication link is enhanced through cooperative jamming, with the
help of multiple jammers. First, a feasibility condition is derived to achieve
a posit... | 1 | 0 | 1 | 0 | 0 | 0 |
Stochastic Calculus with respect to Gaussian Processes: Part I | Stochastic integration \textit{wrt} Gaussian processes has raised strong
interest in recent years, motivated in particular by its applications in
Internet traffic modeling, biomedicine and finance. The aim of this work is to
define and develop a White Noise Theory-based anticipative stochastic calculus
with respect t... | 0 | 0 | 1 | 0 | 0 | 0 |
Path-like integrals of lenght on surfaces of constant curvature | We naturally associate a measurable space of paths to a couple of orthogonal
vector fields over a surface and we integrate the length function over it. This
integral is interpreted as a natural continuous generalization of indirect
influences on finite graphs and can be thought as a tool to capture geometric
informat... | 0 | 0 | 1 | 0 | 0 | 0 |
Automated Synthesis of Divide and Conquer Parallelism | This paper focuses on automated synthesis of divide-and-conquer parallelism,
which is a common parallel programming skeleton supported by many
cross-platform multithreaded libraries. The challenges of producing (manually
or automatically) a correct divide-and-conquer parallel program from a given
sequential code are ... | 1 | 0 | 0 | 0 | 0 | 0 |
Nikol'ski\uı, Jackson and Ul'yanov type inequalities with Muckenhoupt weights | In the present work we prove a Nikol'ski inequality for trigonometric
polynomials and Ul'yanov type inequalities for functions in Lebesgue spaces
with Muckenhoupt weights. Realization result and Jackson inequalities are
obtained. Simultaneous approximation by polynomials is considered. Some uniform
norm inequalities ... | 0 | 0 | 1 | 0 | 0 | 0 |
CosmoGAN: creating high-fidelity weak lensing convergence maps using Generative Adversarial Networks | Inferring model parameters from experimental data is a grand challenge in
many sciences, including cosmology. This often relies critically on high
fidelity numerical simulations, which are prohibitively computationally
expensive. The application of deep learning techniques to generative modeling
is renewing interest ... | 1 | 1 | 0 | 0 | 0 | 0 |
Gaussian approximation of maxima of Wiener functionals and its application to high-frequency data | This paper establishes an upper bound for the Kolmogorov distance between the
maximum of a high-dimensional vector of smooth Wiener functionals and the
maximum of a Gaussian random vector. As a special case, we show that the
maximum of multiple Wiener-Itô integrals with common orders is
well-approximated by its Gauss... | 0 | 0 | 1 | 1 | 0 | 0 |
A Kronecker-type identity and the representations of a number as a sum of three squares | By considering a limiting case of a Kronecker-type identity, we obtain an
identity found by both Andrews and Crandall. We then use the Andrews-Crandall
identity to give a new proof of a formula of Gauss for the representations of a
number as a sum of three squares. From the Kronecker-type identity, we also
deduce Gau... | 0 | 0 | 1 | 0 | 0 | 0 |
DeepTrend: A Deep Hierarchical Neural Network for Traffic Flow Prediction | In this paper, we consider the temporal pattern in traffic flow time series,
and implement a deep learning model for traffic flow prediction. Detrending
based methods decompose original flow series into trend and residual series, in
which trend describes the fixed temporal pattern in traffic flow and residual
series ... | 1 | 0 | 0 | 0 | 0 | 0 |
A new approach to Kaluza-Klein Theory | We propose in this paper a new approach to the Kaluza-Klein idea of a five
dimensional space-time unifying gravitation and electromagnetism, and extension
to higher-dimensional space-time. By considering a natural geometric definition
of a matter fluid and abandoning the usual requirement of a Ricci-flat five
dimensi... | 0 | 0 | 1 | 0 | 0 | 0 |
Density of orbits of dominant regular self-maps of semiabelian varieties | We prove a conjecture of Medvedev and Scanlon in the case of regular
morphisms of semiabelian varieties. That is, if $G$ is a semiabelian variety
defined over an algebraically closed field $K$ of characteristic $0$, and
$\varphi\colon G\to G$ is a dominant regular self-map of $G$ which is not
necessarily a group homo... | 0 | 0 | 1 | 0 | 0 | 0 |
Asymptotic coverage probabilities of bootstrap percentile confidence intervals for constrained parameters | The asymptotic behaviour of the commonly used bootstrap percentile confidence
interval is investigated when the parameters are subject to linear inequality
constraints. We concentrate on the important one- and two-sample problems with
data generated from general parametric distributions in the natural exponential
fam... | 0 | 0 | 1 | 1 | 0 | 0 |
Correlations and enlarged superconducting phase of $t$-$J_\perp$ chains of ultracold molecules on optical lattices | We compute physical properties across the phase diagram of the $t$-$J_\perp$
chain with long-range dipolar interactions, which describe ultracold polar
molecules on optical lattices. Our results obtained by the density-matrix
renormalization group (DMRG) indicate that superconductivity is enhanced when
the Ising comp... | 0 | 1 | 0 | 0 | 0 | 0 |
MinimalRNN: Toward More Interpretable and Trainable Recurrent Neural Networks | We introduce MinimalRNN, a new recurrent neural network architecture that
achieves comparable performance as the popular gated RNNs with a simplified
structure. It employs minimal updates within RNN, which not only leads to
efficient learning and testing but more importantly better interpretability and
trainability. ... | 1 | 0 | 0 | 1 | 0 | 0 |
Boolean quadric polytopes are faces of linear ordering polytopes | Let $BQP(n)$ be a boolean quadric polytope, $LOP(m)$ be a linear ordering
polytope. It is shown that $BQP(n)$ is linearly isomorphic to a face of
$LOP(2n)$.
| 1 | 0 | 0 | 0 | 0 | 0 |
Sparse Matrix Code Dependence Analysis Simplification at Compile Time | Analyzing array-based computations to determine data dependences is useful
for many applications including automatic parallelization, race detection,
computation and communication overlap, verification, and shape analysis. For
sparse matrix codes, array data dependence analysis is made more difficult by
the use of in... | 1 | 0 | 0 | 0 | 0 | 0 |
ICA based on the data asymmetry | Independent Component Analysis (ICA) - one of the basic tools in data
analysis - aims to find a coordinate system in which the components of the data
are independent. Most of existing methods are based on the minimization of the
function of fourth-order moment (kurtosis). Skewness (third-order moment) has
received mu... | 0 | 0 | 1 | 1 | 0 | 0 |
Solid hulls of weighted Banach spaces of analytic functions on the unit disc with exponential weights | We study weighted $H^\infty$ spaces of analytic functions on the open unit
disc in the case of non-doubling weights, which decrease rapidly with respect
to the boundary distance. We characterize the solid hulls of such spaces and
give quite explicit representations of them in the case of the most natural
exponentiall... | 0 | 0 | 1 | 0 | 0 | 0 |
Line bundles defined by the Schwarz function | Cauchy and exponential transforms are characterized, and constructed, as
canonical holomorphic sections of certain line bundles on the Riemann sphere
defined in terms of the Schwarz function. A well known natural connection
between Schwarz reflection and line bundles defined on the Schottky double of a
planar domain ... | 0 | 0 | 1 | 0 | 0 | 0 |
Collisional excitation of NH3 by atomic and molecular hydrogen | We report extensive theoretical calculations on the rotation-inversion
excitation of interstellar ammonia (NH3) due to collisions with atomic and
molecular hydrogen (both para- and ortho-H2). Close-coupling calculations are
performed for total energies in the range 1-2000 cm-1 and rotational cross
sections are obtain... | 0 | 1 | 0 | 0 | 0 | 0 |
Deterministic and Probabilistic Conditions for Finite Completability of Low-rank Multi-View Data | We consider the multi-view data completion problem, i.e., to complete a
matrix $\mathbf{U}=[\mathbf{U}_1|\mathbf{U}_2]$ where the ranks of
$\mathbf{U},\mathbf{U}_1$, and $\mathbf{U}_2$ are given. In particular, we
investigate the fundamental conditions on the sampling pattern, i.e., locations
of the sampled entries f... | 1 | 0 | 1 | 0 | 0 | 0 |
Grid-forming Control for Power Converters based on Matching of Synchronous Machines | We consider the problem of grid-forming control of power converters in
low-inertia power systems. Starting from an average-switch three-phase inverter
model, we draw parallels to a synchronous machine (SM) model and propose a
novel grid-forming converter control strategy which dwells upon the main
characteristic of a... | 0 | 0 | 1 | 0 | 0 | 0 |
Characterizing Dust Attenuation in Local Star-Forming Galaxies: Near-Infrared Reddening and Normalization | We characterize the near-infrared (NIR) dust attenuation for a sample of
~5500 local (z<0.1) star-forming galaxies and obtain an estimate of their
average total-to-selective attenuation $k(\lambda)$. We utilize data from the
United Kingdom Infrared Telescope (UKIRT) and the Two Micron All-Sky Survey
(2MASS), which is... | 0 | 1 | 0 | 0 | 0 | 0 |
Sequential Checking: Reallocation-Free Data-Distribution Algorithm for Scale-out Storage | Using tape or optical devices for scale-out storage is one option for storing
a vast amount of data. However, it is impossible or almost impossible to
rewrite data with such devices. Thus, scale-out storage using such devices
cannot use standard data-distribution algorithms because they rewrite data for
moving betwee... | 1 | 0 | 0 | 0 | 0 | 0 |
Learning with Confident Examples: Rank Pruning for Robust Classification with Noisy Labels | Noisy PN learning is the problem of binary classification when training
examples may be mislabeled (flipped) uniformly with noise rate rho1 for
positive examples and rho0 for negative examples. We propose Rank Pruning (RP)
to solve noisy PN learning and the open problem of estimating the noise rates,
i.e. the fractio... | 1 | 0 | 0 | 1 | 0 | 0 |
code2vec: Learning Distributed Representations of Code | We present a neural model for representing snippets of code as continuous
distributed vectors ("code embeddings"). The main idea is to represent a code
snippet as a single fixed-length $\textit{code vector}$, which can be used to
predict semantic properties of the snippet. This is performed by decomposing
code to a c... | 1 | 0 | 0 | 1 | 0 | 0 |
Learning a Local Feature Descriptor for 3D LiDAR Scans | Robust data association is necessary for virtually every SLAM system and
finding corresponding points is typically a preprocessing step for scan
alignment algorithms. Traditionally, handcrafted feature descriptors were used
for these problems but recently learned descriptors have been shown to perform
more robustly. ... | 1 | 0 | 0 | 0 | 0 | 0 |
Dynamical tides in exoplanetary systems containing Hot Jupiters: confronting theory and observations | We study the effect of dynamical tides associated with the excitation of
gravity waves in an interior radiative region of the central star on orbital
evolution in observed systems containing Hot Jupiters. We consider WASP-43,
Ogle-tr-113, WASP-12, and WASP-18 which contain stars on the main sequence
(MS). For these s... | 0 | 1 | 0 | 0 | 0 | 0 |
Metastability versus collapse following a quench in attractive Bose-Einstein condensates | We consider a Bose-Einstein condensate (BEC) with attractive two-body
interactions in a cigar-shaped trap, initially prepared in its ground state for
a given negative scattering length, which is quenched to a larger absolute
value of the scattering length. Using the mean-field approximation, we compute
numerically, f... | 0 | 1 | 0 | 0 | 0 | 0 |
A similarity criterion for sequential programs using truth-preserving partial functions | The execution of sequential programs allows them to be represented using
mathematical functions formed by the composition of statements following one
after the other. Each such statement is in itself a partial function, which
allows only inputs satisfying a particular Boolean condition to carry forward
the execution ... | 1 | 0 | 0 | 0 | 0 | 0 |
Subsampling large graphs and invariance in networks | Specify a randomized algorithm that, given a very large graph or network,
extracts a random subgraph. What can we learn about the input graph from a
single subsample? We derive laws of large numbers for the sampler output, by
relating randomized subsampling to distributional invariance: Assuming an
invariance holds i... | 0 | 0 | 1 | 1 | 0 | 0 |
Taylor coefficients of non-holomorphic Jacobi forms and applications | In this paper, we prove modularity results of Taylor coefficients of certain
non-holomorphic Jacobi forms. It is well-known that Taylor coefficients of
holomorphic Jacobi forms are quasimoular forms. However recently there has been
a wide interest for Taylor coefficients of non-holomorphic Jacobi forms for
example ar... | 0 | 0 | 1 | 0 | 0 | 0 |
Beamspace SU-MIMO for Future Millimeter Wave Wireless Communications | For future networks (i.e., the fifth generation (5G) wireless networks and
beyond), millimeter-wave (mmWave) communication with large available unlicensed
spectrum is a promising technology that enables gigabit multimedia
applications. Thanks to the short wavelength of mmWave radio, massive antenna
arrays can be pack... | 1 | 0 | 0 | 0 | 0 | 0 |
Learning Robust Visual-Semantic Embeddings | Many of the existing methods for learning joint embedding of images and text
use only supervised information from paired images and its textual attributes.
Taking advantage of the recent success of unsupervised learning in deep neural
networks, we propose an end-to-end learning framework that is able to extract
more ... | 1 | 0 | 0 | 0 | 0 | 0 |
Quantitative estimates of the surface habitability of Kepler-452b | Kepler-452b is currently the best example of an Earth-size planet in the
habitable zone of a sun-like star, a type of planet whose number of detections
is expected to increase in the future. Searching for biosignatures in the
supposedly thin atmospheres of these planets is a challenging goal that
requires a careful s... | 0 | 1 | 0 | 0 | 0 | 0 |
Design and implementation of dynamic logic gates and R-S flip-flop using quasiperiodically driven Murali-Lakshmanan-Chua circuit | We report the propagation of a square wave signal in a quasi-periodically
driven Murali-Lakshmanan-Chua (QPDMLC) circuit system. It is observed that
signal propagation is possible only above a certain threshold strength of the
square wave or digital signal and all the values above the threshold amplitude
are termed a... | 0 | 1 | 0 | 0 | 0 | 0 |
Sequential Attend, Infer, Repeat: Generative Modelling of Moving Objects | We present Sequential Attend, Infer, Repeat (SQAIR), an interpretable deep
generative model for videos of moving objects. It can reliably discover and
track objects throughout the sequence of frames, and can also generate future
frames conditioning on the current frame, thereby simulating expected motion of
objects. ... | 0 | 0 | 0 | 1 | 0 | 0 |
Learning Local Shape Descriptors from Part Correspondences With Multi-view Convolutional Networks | We present a new local descriptor for 3D shapes, directly applicable to a
wide range of shape analysis problems such as point correspondences, semantic
segmentation, affordance prediction, and shape-to-scan matching. The descriptor
is produced by a convolutional network that is trained to embed geometrically
and sema... | 1 | 0 | 0 | 0 | 0 | 0 |
Alternating minimization for dictionary learning with random initialization | We present theoretical guarantees for an alternating minimization algorithm
for the dictionary learning/sparse coding problem. The dictionary learning
problem is to factorize vector samples $y^{1},y^{2},\ldots, y^{n}$ into an
appropriate basis (dictionary) $A^*$ and sparse vectors $x^{1*},\ldots,x^{n*}$.
Our algorith... | 1 | 0 | 0 | 1 | 0 | 0 |
Optimal Transmission Line Switching under Geomagnetic Disturbances | In recent years, there have been increasing concerns about how geomagnetic
disturbances (GMDs) impact electrical power systems. Geomagnetically-induced
currents (GICs) can saturate transformers, induce hot spot heating and increase
reactive power losses. These effects can potentially cause catastrophic damage
to tran... | 1 | 0 | 0 | 0 | 0 | 0 |
Image Forgery Localization Based on Multi-Scale Convolutional Neural Networks | In this paper, we propose to utilize Convolutional Neural Networks (CNNs) and
the segmentation-based multi-scale analysis to locate tampered areas in digital
images. First, to deal with color input sliding windows of different scales, a
unified CNN architecture is designed. Then, we elaborately design the training
pr... | 1 | 0 | 0 | 0 | 0 | 0 |
The QKP limit of the quantum Euler-Poisson equation | In this paper, we consider the derivation of the Kadomtsev-Petviashvili (KP)
equation for cold ion-acoustic wave in the long wavelength limit of the
two-dimensional quantum Euler-Poisson system, under different scalings for
varying directions in the Gardner-Morikawa transform. It is shown that the
types of the KP equ... | 0 | 0 | 1 | 0 | 0 | 0 |
Variational Implicit Processes | This paper introduces the variational implicit processes (VIPs), a Bayesian
nonparametric method based on a class of highly flexible priors over functions.
Similar to Gaussian processes (GPs), in implicit processes (IPs), an implicit
multivariate prior (data simulators, Bayesian neural networks, etc.) is placed
over ... | 0 | 0 | 0 | 1 | 0 | 0 |
Silicon Micromachined High-contrast Artificial Dielectrics for Millimeter-wave Transformation Optics Antennas | Transformation optics methods and gradient index electromagnetic structures
rely upon spatially varied arbitrary permittivity. This, along with recent
interest in millimeter-wave lens-based antennas demands high spatial resolution
dielectric variation. Perforated media have been used to fabricate gradient
index struc... | 0 | 1 | 0 | 0 | 0 | 0 |
Pseudogap and Fermi surface in the presence of spin-vortex checkerboard for 1/8-doped lanthanum cuprates | Lanthanum family of high-temperature cuprate superconductors is known to
exhibit both spin and charge electronic modulations around doping level 1/8. We
assume that these modulations have the character of two-dimensional spin-vortex
checkerboard and investigate whether this assumption is consistent with the
Fermi sur... | 0 | 1 | 0 | 0 | 0 | 0 |
Revealing the cluster of slow transients behind a large slow slip event | Capable of reaching similar magnitudes to large megathrust earthquakes
($M_w>7$), slow slip events play a major role in accommodating tectonic motion
on plate boundaries. These slip transients are the slow release of built-up
tectonic stress that are geodetically imaged as a predominantly aseismic
rupture, which is s... | 0 | 1 | 0 | 0 | 0 | 0 |
General $N$-solitons and their dynamics in several nonlocal nonlinear Schrödinger equations | General $N$-solitons in three recently-proposed nonlocal nonlinear
Schrödinger equations are presented. These nonlocal equations include the
reverse-space, reverse-time, and reverse-space-time nonlinear Schrödinger
equations, which are nonlocal reductions of the Ablowitz-Kaup-Newell-Segur
(AKNS) hierarchy. It is show... | 0 | 1 | 0 | 0 | 0 | 0 |
Revisiting wireless network jamming by SIR-based considerations and Multiband Robust Optimization | We revisit the mathematical models for wireless network jamming introduced by
Commander et al.: we first point out the strong connections with classical
wireless network design and then we propose a new model based on the explicit
use of signal-to-interference quantities. Moreover, to address the intrinsic
uncertain ... | 1 | 0 | 1 | 0 | 0 | 0 |
New models for symbolic data analysis | Symbolic data analysis (SDA) is an emerging area of statistics based on
aggregating individual level data into group-based distributional summaries
(symbols), and then developing statistical methods to analyse them. It is ideal
for analysing large and complex datasets, and has immense potential to become a
standard i... | 0 | 0 | 0 | 1 | 0 | 0 |
Soft Methodology for Cost-and-error Sensitive Classification | Many real-world data mining applications need varying cost for different
types of classification errors and thus call for cost-sensitive classification
algorithms. Existing algorithms for cost-sensitive classification are
successful in terms of minimizing the cost, but can result in a high error rate
as the trade-off... | 1 | 0 | 0 | 0 | 0 | 0 |
Raman LIDARs and atmospheric calibration for the Cherenkov Telescope Array | The Cherenkov Telescope Array (CTA) is the next generation of Imaging
Atmospheric Cherenkov Telescopes. It will reach a sensitivity and energy
resolution never obtained until now by any other high energy gamma-ray
experiment. Understanding the systematic uncertainties in general will be a
crucial issue for the perfor... | 0 | 1 | 0 | 0 | 0 | 0 |
Generalized notions of sparsity and restricted isometry property. Part II: Applications | The restricted isometry property (RIP) is a universal tool for data recovery.
We explore the implication of the RIP in the framework of generalized sparsity
and group measurements introduced in the Part I paper. It turns out that for a
given measurement instrument the number of measurements for RIP can be improved
by... | 0 | 0 | 0 | 1 | 0 | 0 |
Mellin-Meijer-kernel density estimation on $\mathbb{R}^+$ | Nonparametric kernel density estimation is a very natural procedure which
simply makes use of the smoothing power of the convolution operation. Yet, it
performs poorly when the density of a positive variable is to be estimated
(boundary issues, spurious bumps in the tail). So various extensions of the
basic kernel es... | 0 | 0 | 1 | 1 | 0 | 0 |
Gene Ontology (GO) Prediction using Machine Learning Methods | We applied machine learning to predict whether a gene is involved in axon
regeneration. We extracted 31 features from different databases and trained
five machine learning models. Our optimal model, a Random Forest Classifier
with 50 submodels, yielded a test score of 85.71%, which is 4.1% higher than
the baseline sc... | 1 | 0 | 0 | 1 | 0 | 0 |
Dimension Spectra of Lines | This paper investigates the algorithmic dimension spectra of lines in the
Euclidean plane. Given any line L with slope a and vertical intercept b, the
dimension spectrum sp(L) is the set of all effective Hausdorff dimensions of
individual points on L. We draw on Kolmogorov complexity and geometrical
arguments to show... | 1 | 0 | 0 | 0 | 0 | 0 |
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