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 |
|---|---|---|---|---|---|---|---|
Beyond Shared Hierarchies: Deep Multitask Learning through Soft Layer Ordering | Existing deep multitask learning (MTL) approaches align layers shared between
tasks in a parallel ordering. Such an organization significantly constricts the
types of shared structure that can be learned. The necessity of parallel
ordering for deep MTL is first tested by comparing it with permuted ordering of
shared ... | 1 | 0 | 0 | 1 | 0 | 0 |
Relational Algebra for In-Database Process Mining | The execution logs that are used for process mining in practice are often
obtained by querying an operational database and storing the result in a flat
file. Consequently, the data processing power of the database system cannot be
used anymore for this information, leading to constrained flexibility in the
definition... | 1 | 0 | 0 | 0 | 0 | 0 |
Global existence for the nonlinear fractional Schrödinger equation with fractional dissipation | We consider the initial value problem for the fractional nonlinear
Schrödinger equation with a fractional dissipation. Global existence and
scattering are proved depending on the order of the fractional dissipation.
| 0 | 0 | 1 | 0 | 0 | 0 |
Statistical properties of an enstrophy conserving discretisation for the stochastic quasi-geostrophic equation | A framework of variational principles for stochastic fluid dynamics was
presented by Holm (2015), and these stochastic equations were also derived by
Cotter et al. (2017). We present a conforming finite element discretisation for
the stochastic quasi-geostrophic equation that was derived from this framework.
The disc... | 0 | 1 | 0 | 0 | 0 | 0 |
Conditional Optimal Stopping: A Time-Inconsistent Optimization | Inspired by recent work of P.-L. Lions on conditional optimal control, we
introduce a problem of optimal stopping under bounded rationality: the
objective is the expected payoff at the time of stopping, conditioned on
another event. For instance, an agent may care only about states where she is
still alive at the tim... | 0 | 0 | 0 | 0 | 0 | 1 |
Principles for optimal cooperativity in allosteric materials | Allosteric proteins transmit a mechanical signal induced by binding a ligand.
However, understanding the nature of the information transmitted and the
architectures optimizing such transmission remains a challenge. Here we show
using an {\it in-silico} evolution scheme and theoretical arguments that
architectures opt... | 0 | 1 | 0 | 0 | 0 | 0 |
Improved electronic structure and magnetic exchange interactions in transition metal oxides | We discuss the application of the Agapito Curtarolo and Buongiorno Nardelli
(ACBN0) pseudo-hybrid Hubbard density functional to several transition metal
oxides. ACBN0 is a fast, accurate and parameter-free alternative to traditional
DFT+$U$ and hybrid exact exchange methods. In ACBN0, the Hubbard energy of
DFT+$U$ is... | 0 | 1 | 0 | 0 | 0 | 0 |
Test of SensL SiPM coated with NOL-1 wavelength shifter in liquid xenon | A SensL MicroFC-SMT-60035 6x6 mm$^2$ silicon photo-multiplier coated with a
NOL-1 wavelength shifter have been tested in the liquid xenon to detect the
175-nm scintillation light. For comparison, a Hamamatsu vacuum ultraviolet
sensitive MPPC VUV3 3x3 mm$^2$ was tested under the same conditions. The
photodetection eff... | 0 | 1 | 0 | 0 | 0 | 0 |
Neon2: Finding Local Minima via First-Order Oracles | We propose a reduction for non-convex optimization that can (1) turn an
stationary-point finding algorithm into an local-minimum finding one, and (2)
replace the Hessian-vector product computations with only gradient
computations. It works both in the stochastic and the deterministic settings,
without hurting the alg... | 1 | 0 | 0 | 1 | 0 | 0 |
Geometrical Insights for Implicit Generative Modeling | Learning algorithms for implicit generative models can optimize a variety of
criteria that measure how the data distribution differs from the implicit model
distribution, including the Wasserstein distance, the Energy distance, and the
Maximum Mean Discrepancy criterion. A careful look at the geometries induced by
th... | 1 | 0 | 0 | 1 | 0 | 0 |
Simple Countermeasures to Mitigate the Effect of Pollution Attack in Network Coding Based Peer-to-Peer Live Streaming | Network coding based peer-to-peer streaming represents an effective solution
to aggregate user capacities and to increase system throughput in live
multimedia streaming. Nonetheless, such systems are vulnerable to pollution
attacks where a handful of malicious peers can disrupt the communication by
transmitting just ... | 1 | 0 | 0 | 0 | 0 | 0 |
Small-scale structure and the Lyman-$α$ forest baryon acoustic oscillation feature | The baryon-acoustic oscillation (BAO) feature in the Lyman-$\alpha$ forest is
one of the key probes of the cosmic expansion rate at redshifts z~2.5, well
before dark energy is believed to have become dynamically significant. A key
advantage of the BAO as a standard ruler is that it is a sharp feature and
hence is mor... | 0 | 1 | 0 | 0 | 0 | 0 |
Scale-dependent perturbations finally detectable by future galaxy surveys and their contribution to cosmological model selection | By means of the present geometrical and dynamical observational data, it is
very hard to establish, from a statistical perspective, a clear preference
among the vast majority of the proposed models for the dynamical dark energy
and/or modified gravity theories alternative with respect to the $\Lambda$CDM
scenario. On... | 0 | 1 | 0 | 0 | 0 | 0 |
InfoCatVAE: Representation Learning with Categorical Variational Autoencoders | This paper describes InfoCatVAE, an extension of the variational autoencoder
that enables unsupervised disentangled representation learning. InfoCatVAE uses
multimodal distributions for the prior and the inference network and then
maximizes the evidence lower bound objective (ELBO). We connect the new ELBO
derived fo... | 0 | 0 | 0 | 1 | 0 | 0 |
Quadratic twists of abelian varieties and disparity in Selmer ranks | We study the parity of 2-Selmer ranks in the family of quadratic twists of a
fixed principally polarised abelian variety over a number field. Specifically,
we determine the proportion of twists having odd (resp. even) 2-Selmer rank.
This generalises work of Klagsbrun--Mazur--Rubin for elliptic curves and Yu for
Jacob... | 0 | 0 | 1 | 0 | 0 | 0 |
From acquaintance to best friend forever: robust and fine-grained inference of social tie strengths | Social networks often provide only a binary perspective on social ties: two
individuals are either connected or not. While sometimes external information
can be used to infer the strength of social ties, access to such information
may be restricted or impractical. Sintos and Tsaparas (KDD 2014) first
suggested to inf... | 1 | 0 | 0 | 0 | 0 | 0 |
Conditional bias robust estimation of the total of curve data by sampling in a finite population: an illustration on electricity load curves | For marketing or power grid management purposes, many studies based on the
analysis of the total electricity consumption curves of groups of customers are
now carried out by electricity companies. Aggregated total or mean load curves
are estimated using individual curves measured at fine time grid and collected
accor... | 0 | 0 | 0 | 1 | 0 | 0 |
Ulrich bundles on smooth projective varieties of minimal degree | We classify the Ulrich vector bundles of arbitrary rank on smooth projective
varieties of minimal degree. In the process, we prove the stability of the
sheaves of relative differentials on rational scrolls.
| 0 | 0 | 1 | 0 | 0 | 0 |
$k$-shellable simplicial complexes and graphs | In this paper we show that a $k$-shellable simplicial complex is the
expansion of a shellable complex. We prove that the face ring of a pure
$k$-shellable simplicial complex satisfies the Stanley conjecture. In this way,
by applying expansion functor to the face ring of a given pure shellable
complex, we construct a ... | 0 | 0 | 1 | 0 | 0 | 0 |
The Effect of Phasor Measurement Units on the Accuracy of the Network Estimated Variables | The most commonly used weighted least square state estimator in power
industry is nonlinear and formulated by using conventional measurements such as
line flow and injection measurements. PMUs (Phasor Measurement Units) are
gradually adding them to improve the state estimation process. In this paper
the way of corpor... | 1 | 0 | 1 | 0 | 0 | 0 |
$ε$-Regularity and Structure of 4-dimensional Shrinking Ricci Solitons | A closed four dimensional manifold cannot possess a non-flat Ricci soliton
metric with arbitrarily small $L^2$-norm of the curvature. In this paper, we
localize this fact in the case of shrinking Ricci solitons by proving an
$\varepsilon$-regularity theorem, thus confirming a conjecture of Cheeger-Tian.
As applicatio... | 0 | 0 | 1 | 0 | 0 | 0 |
Cosmological model discrimination with Deep Learning | We demonstrate the potential of Deep Learning methods for measurements of
cosmological parameters from density fields, focusing on the extraction of
non-Gaussian information. We consider weak lensing mass maps as our dataset. We
aim for our method to be able to distinguish between five models, which were
chosen to li... | 0 | 1 | 0 | 1 | 0 | 0 |
Deep Memory Networks for Attitude Identification | We consider the task of identifying attitudes towards a given set of entities
from text. Conventionally, this task is decomposed into two separate subtasks:
target detection that identifies whether each entity is mentioned in the text,
either explicitly or implicitly, and polarity classification that classifies
the e... | 1 | 0 | 0 | 0 | 0 | 0 |
Discrete flow posteriors for variational inference in discrete dynamical systems | Each training step for a variational autoencoder (VAE) requires us to sample
from the approximate posterior, so we usually choose simple (e.g. factorised)
approximate posteriors in which sampling is an efficient computation that fully
exploits GPU parallelism. However, such simple approximate posteriors are often
ins... | 0 | 0 | 0 | 1 | 1 | 0 |
Audio Super Resolution using Neural Networks | We introduce a new audio processing technique that increases the sampling
rate of signals such as speech or music using deep convolutional neural
networks. Our model is trained on pairs of low and high-quality audio examples;
at test-time, it predicts missing samples within a low-resolution signal in an
interpolation... | 1 | 0 | 0 | 0 | 0 | 0 |
Thermoelectric power factor enhancement by spin-polarized currents - a nanowire case study | Thermoelectric (TE) measurements have been performed on the workhorses of
today's data storage devices, exhibiting either the giant or the anisotropic
magnetoresistance effect (GMR and AMR). The temperature-dependent (50-300 K)
and magnetic field-dependent (up to 1 T) TE power factor (PF) has been
determined for seve... | 0 | 1 | 0 | 0 | 0 | 0 |
Risk-Sensitive Cooperative Games for Human-Machine Systems | Autonomous systems can substantially enhance a human's efficiency and
effectiveness in complex environments. Machines, however, are often unable to
observe the preferences of the humans that they serve. Despite the fact that
the human's and machine's objectives are aligned, asymmetric information, along
with heteroge... | 1 | 0 | 0 | 1 | 0 | 0 |
A natural framework for isogeometric fluid-structure interaction based on BEM-shell coupling | The interaction between thin structures and incompressible Newtonian fluids
is ubiquitous both in nature and in industrial applications. In this paper we
present an isogeometric formulation of such problems which exploits a boundary
integral formulation of Stokes equations to model the surrounding flow, and a
non lin... | 0 | 1 | 1 | 0 | 0 | 0 |
Inertial Effects on the Stress Generation of Active Fluids | Suspensions of self-propelled bodies generate a unique mechanical stress
owing to their motility that impacts their large-scale collective behavior. For
microswimmers suspended in a fluid with negligible particle inertia, we have
shown that the virial `swim stress' is a useful quantity to understand the
rheology and ... | 0 | 1 | 0 | 0 | 0 | 0 |
On Gauge Invariance and Covariant Derivatives in Metric Spaces | In this manuscript, we will discuss the construction of covariant derivative
operator in quantum gravity. We will find it is appropriate to use affine
connections more general than metric compatible connections in quantum gravity.
We will demonstrate this using the canonical quantization procedure. This is
valid irre... | 0 | 1 | 0 | 0 | 0 | 0 |
A Compressed Sensing Approach for Distribution Matching | In this work, we formulate the fixed-length distribution matching as a
Bayesian inference problem. Our proposed solution is inspired from the
compressed sensing paradigm and the sparse superposition (SS) codes. First, we
introduce sparsity in the binary source via position modulation (PM). We then
present a simple an... | 0 | 0 | 0 | 1 | 0 | 0 |
A simple descriptor and predictor for the stable structures of two-dimensional surface alloys | Predicting the ground state of alloy systems is challenging due to the large
number of possible configurations. We identify an easily computed descriptor
for the stability of binary surface alloys, the effective coordination number
$\mathscr{E}$. We show that $\mathscr{E}(M)$ correlates well with the enthalpy
of mixi... | 0 | 1 | 0 | 0 | 0 | 0 |
Fractional integrals and Fourier transforms | This paper gives a short survey of some basic results related to estimates of
fractional integrals and Fourier transforms. It is closely adjoint to our
previous survey papers \cite{K1998} and \cite{K2007}. The main methods used in
the paper are based on nonincreasing rearrangements. We give alternative proofs
of some... | 0 | 0 | 1 | 0 | 0 | 0 |
Multi-Level Network Embedding with Boosted Low-Rank Matrix Approximation | As opposed to manual feature engineering which is tedious and difficult to
scale, network representation learning has attracted a surge of research
interests as it automates the process of feature learning on graphs. The
learned low-dimensional node vector representation is generalizable and eases
the knowledge disco... | 1 | 0 | 0 | 1 | 0 | 0 |
Deviation from the dipole-ice model in the new spinel spin-ice candidate, MgEr$_2$Se$_4$ | In spin ice research, small variations in structure or interactions drive a
multitude of different behaviors, yet the collection of known materials relies
heavily on the `227' pyrochlore structure. Here, we present thermodynamic,
structural and inelastic neutron scattering data on a new spin-ice material,
MgEr$_2$Se$... | 0 | 1 | 0 | 0 | 0 | 0 |
Generating Nontrivial Melodies for Music as a Service | We present a hybrid neural network and rule-based system that generates pop
music. Music produced by pure rule-based systems often sounds mechanical. Music
produced by machine learning sounds better, but still lacks hierarchical
temporal structure. We restore temporal hierarchy by augmenting machine
learning with a t... | 1 | 0 | 0 | 0 | 0 | 0 |
Vision and Challenges for Knowledge Centric Networking (KCN) | In the creation of a smart future information society, Internet of Things
(IoT) and Content Centric Networking (CCN) break two key barriers for both the
front-end sensing and back-end networking. However, we still observe the
missing piece of the research that dominates the current networking traffic
control and syst... | 1 | 0 | 0 | 0 | 0 | 0 |
Extracting Geometry from Quantum Spacetime: Obstacles down the road | Any acceptable quantum gravity theory must allow us to recover the classical
spacetime in the appropriate limit. Moreover, the spacetime geometrical notions
should be intrinsically tied to the behavior of the matter that probes them. We
consider some difficulties that would be confronted in attempting such an
enterpr... | 0 | 1 | 0 | 0 | 0 | 0 |
Data-Driven Estimation of Travel Latency Cost Functions via Inverse Optimization in Multi-Class Transportation Networks | We develop a method to estimate from data travel latency cost functions in
multi-class transportation networks, which accommodate different types of
vehicles with very different characteristics (e.g., cars and trucks).
Leveraging our earlier work on inverse variational inequalities, we develop a
data-driven approach ... | 1 | 0 | 1 | 0 | 0 | 0 |
Autoencoder Based Sample Selection for Self-Taught Learning | Self-taught learning is a technique that uses a large number of unlabeled
data as source samples to improve the task performance on target samples.
Compared with other transfer learning techniques, self-taught learning can be
applied to a broader set of scenarios due to the loose restrictions on source
data. However,... | 0 | 0 | 0 | 1 | 0 | 0 |
Guiding Chemical Synthesis: Computational Prediction of the Regioselectivity of CH Functionalization | We will develop a computational method (RegioSQM) for predicting the
regioselectivity of CH functionalization reactions that can be used by
synthetic chemists who are not experts in computational chemistry through a
simple web interface (regiosqm.org). CH functionalization, i.e. replacing the
hydrogen atom in a CH bo... | 0 | 1 | 0 | 0 | 0 | 0 |
Potential-Function Proofs for First-Order Methods | This note discusses proofs for convergence of first-order methods based on
simple potential-function arguments. We cover methods like gradient descent
(for both smooth and non-smooth settings), mirror descent, and some accelerated
variants.
| 1 | 0 | 0 | 0 | 0 | 0 |
Multidimensional $p$-adic continued fraction algorithms | We give a new class of multidimensional $p$-adic continued fraction
algorithms. We propose an algorithm in the class for which we can expect that
multidimensional $p$-adic version of Lagrange's Theorem holds.
| 0 | 0 | 1 | 0 | 0 | 0 |
Shutting down or powering up a (U)LIRG? Merger components in distinctly different evolutionary states in IRAS 19115-2124 (The Bird) | We present new SINFONI near-infrared integral field unit (IFU) spectroscopy
and SALT optical long-slit spectroscopy characterising the history of a nearby
merging luminous infrared galaxy, dubbed the Bird (IRAS19115-2114). The NIR
line-ratio maps of the IFU data-cubes and stellar population fitting of the
SALT spectr... | 0 | 1 | 0 | 0 | 0 | 0 |
Asymptotics to all orders of the Hurwitz zeta function | We present several formulae for the large-$t$ asymptotics of the modified
Hurwitz zeta function $\zeta_1(x,s),x>0,s=\sigma+it,0<\sigma\leq1,t>0,$ which
are valid to all orders. In the case of $x=0$, these formulae reduce to the
asymptotic expressions recently obtained for the Riemann zeta function, which
include the ... | 0 | 0 | 1 | 0 | 0 | 0 |
Distributed Stochastic Approximation with Local Projections | We propose a distributed version of a stochastic approximation scheme
constrained to remain in the intersection of a finite family of convex sets.
The projection to the intersection of these sets is also computed in a
distributed manner and a `nonlinear gossip' mechanism is employed to blend the
projection iterations... | 1 | 0 | 0 | 0 | 0 | 0 |
Expected Policy Gradients | We propose expected policy gradients (EPG), which unify stochastic policy
gradients (SPG) and deterministic policy gradients (DPG) for reinforcement
learning. Inspired by expected sarsa, EPG integrates across the action when
estimating the gradient, instead of relying only on the action in the sampled
trajectory. We ... | 1 | 0 | 0 | 1 | 0 | 0 |
A new Hysteretic Nonlinear Energy Sink (HNES) | The behavior of a new Hysteretic Nonlinear Energy Sink (HNES) coupled to a
linear primary oscillator is investigated in shock mitigation. Apart from a
small mass and a nonlinear elastic spring of the Duffing oscillator, the HNES
is also comprised of a purely hysteretic and a linear elastic spring of
potentially negat... | 0 | 1 | 0 | 0 | 0 | 0 |
Ultra-Low Noise Amplifier Design for Magnetic Resonance Imaging systems | This paper demonstrates designing and developing of an Ultra-Low Noise
Amplifier which should potentially increase the sensitivity of the existing
Magnetic Resonance Imaging (MRI) systems. The Design of the LNA is fabricated
and characterized including matching and input high power protection circuits.
The estimate i... | 0 | 1 | 0 | 0 | 0 | 0 |
Virtual Astronaut for Scientific Visualization - A Prototype for Santa Maria Crater on Mars | To support scientific visualization of multiple-mission data from Mars, the
Virtual Astronaut (VA) creates an interactive virtual 3D environment built on
the Unity3D Game Engine. A prototype study was conducted based on orbital and
Opportunity Rover data covering Santa Maria Crater in Meridiani Planum on Mars.
The VA... | 1 | 1 | 0 | 0 | 0 | 0 |
Self-Supervised Generalisation with Meta Auxiliary Learning | Learning with auxiliary tasks has been shown to improve the generalisation of
a primary task. However, this comes at the cost of manually-labelling
additional tasks which may, or may not, be useful for the primary task. We
propose a new method which automatically learns labels for an auxiliary task,
such that any sup... | 1 | 0 | 0 | 1 | 0 | 0 |
Measuring High-Energy Spectra with HAWC | The High-Altitude Water-Cherenkov (HAWC) experiment is a TeV $\gamma$-ray
observatory located \unit[4100]{m} above sea level on the Sierra Negra mountain
in Puebla, Mexico. The detector consists of 300 water-filled tanks, each
instrumented with 4 photomultiplier tubes that utilize the water-Cherenkov
technique to det... | 0 | 1 | 0 | 0 | 0 | 0 |
A Study on Arbitrarily Varying Channels with Causal Side Information at the Encoder | In this work, we study two models of arbitrarily varying channels, when
causal side information is available at the encoder in a causal manner. First,
we study the arbitrarily varying channel (AVC) with input and state
constraints, when the encoder has state information in a causal manner. Lower
and upper bounds on t... | 1 | 0 | 1 | 0 | 0 | 0 |
On the Three Properties of Stationary Populations and knotting with Non-Stationary Populations | We propose three properties that are related to the stationary population
identity (SPI) of population biology by connecting it with stationary
populations and non-stationary populations which are approaching stationarity.
These properties provide deeper insights into cohort formation in real-world
populations and th... | 0 | 0 | 0 | 0 | 1 | 0 |
Generating and designing DNA with deep generative models | We propose generative neural network methods to generate DNA sequences and
tune them to have desired properties. We present three approaches: creating
synthetic DNA sequences using a generative adversarial network; a DNA-based
variant of the activation maximization ("deep dream") design method; and a
joint procedure ... | 1 | 0 | 0 | 1 | 0 | 0 |
Radon background in liquid xenon detectors | The radioactive daughters isotope of 222Rn are one of the highest risk
contaminants in liquid xenon detectors aiming for a small signal rate. The
noble gas is permanently emanated from the detector surfaces and mixed with the
xenon target. Because of its long half-life 222Rn is homogeneously distributed
in the target... | 0 | 1 | 0 | 0 | 0 | 0 |
Minimax Regret Bounds for Reinforcement Learning | We consider the problem of provably optimal exploration in reinforcement
learning for finite horizon MDPs. We show that an optimistic modification to
value iteration achieves a regret bound of $\tilde{O}( \sqrt{HSAT} +
H^2S^2A+H\sqrt{T})$ where $H$ is the time horizon, $S$ the number of states,
$A$ the number of acti... | 1 | 0 | 0 | 1 | 0 | 0 |
Asymptotic Theory for the Maximum of an Increasing Sequence of Parametric Functions | \cite{HillMotegi2017} present a new general asymptotic theory for the maximum
of a random array $\{\mathcal{X}_{n}(i)$ $:$ $1$ $\leq $ $i$ $\leq $
$\mathcal{L}\}_{n\geq 1}$, where each $\mathcal{X}_{n}(i)$ is assumed to
converge in probability as $n$ $\rightarrow $ $\infty $. The array dimension
$\mathcal{L}$ is allo... | 0 | 0 | 1 | 1 | 0 | 0 |
Resilient Active Information Gathering with Mobile Robots | Applications of safety, security, and rescue in robotics, such as multi-robot
target tracking, involve the execution of information acquisition tasks by
teams of mobile robots. However, in failure-prone or adversarial environments,
robots get attacked, their communication channels get jammed, and their sensors
may fa... | 1 | 0 | 0 | 1 | 0 | 0 |
Optical properties of a four-layer waveguiding nanocomposite structure in near-IR regime | The theoretical study of the optical properties of TE- and TM- modes in a
four-layer structure composed of the magneto-optical yttrium iron garnet
guiding layer on a dielectric substrate covered by planar nanocomposite guiding
multilayer is presented. The dispersion equation is obtained taking into
account the bigyro... | 0 | 1 | 0 | 0 | 0 | 0 |
High Dimensional Structured Superposition Models | High dimensional superposition models characterize observations using
parameters which can be written as a sum of multiple component parameters, each
with its own structure, e.g., sum of low rank and sparse matrices, sum of
sparse and rotated sparse vectors, etc. In this paper, we consider general
superposition model... | 1 | 0 | 0 | 1 | 0 | 0 |
Source Forager: A Search Engine for Similar Source Code | Developers spend a significant amount of time searching for code: e.g., to
understand how to complete, correct, or adapt their own code for a new context.
Unfortunately, the state of the art in code search has not evolved much beyond
text search over tokenized source. Code has much richer structure and semantics
than... | 1 | 0 | 0 | 0 | 0 | 0 |
Crossmatching variable objects with the Gaia data | Tens of millions of new variable objects are expected to be identified in
over a billion time series from the Gaia mission. Crossmatching known variable
sources with those from Gaia is crucial to incorporate current knowledge,
understand how these objects appear in the Gaia data, train supervised
classifiers to recog... | 0 | 1 | 0 | 0 | 0 | 0 |
A New Test of Multivariate Nonlinear Causality | The multivariate nonlinear Granger causality developed by Bai et al. (2010)
plays an important role in detecting the dynamic interrelationships between two
groups of variables. Following the idea of Hiemstra-Jones (HJ) test proposed by
Hiemstra and Jones (1994), they attempt to establish a central limit theorem
(CLT)... | 0 | 0 | 0 | 1 | 0 | 0 |
Nonlinear dynamics of polar regions in paraelectric phase of (Ba1-x,Srx)TiO3 ceramics | The dynamic dielectric nonlinearity of barium strontium titanate
(Ba1-x,Srx)TiO3 ceramics is investigated in their paraelectric phase. With the
goal to contribute to the identification of the mechanisms that govern the
dielectric nonlinearity in this family, we analyze the amplitude and the phase
angles of the first ... | 0 | 1 | 0 | 0 | 0 | 0 |
Nonlinear Modal Decoupling Based Power System Transient Stability Analysis | Nonlinear modal decoupling (NMD) was recently proposed to nonlinearly
transform a multi-oscillator system into a number of decoupled oscillators
which together behave the same as the original system in an extended
neighborhood of the equilibrium. Each oscillator has just one degree of freedom
and hence can easily be ... | 1 | 0 | 0 | 0 | 0 | 0 |
KELT-18b: Puffy Planet, Hot Host, Probably Perturbed | We report the discovery of KELT-18b, a transiting hot Jupiter in a 2.87d
orbit around the bright (V=10.1), hot, F4V star BD+60 1538 (TYC 3865-1173-1).
We present follow-up photometry, spectroscopy, and adaptive optics imaging that
allow a detailed characterization of the system. Our preferred model fits yield
a host ... | 0 | 1 | 0 | 0 | 0 | 0 |
BAMBI: An R package for Fitting Bivariate Angular Mixture Models | Statistical analyses of directional or angular data have applications in a
variety of fields, such as geology, meteorology and bioinformatics. There is
substantial literature on descriptive and inferential techniques for univariate
angular data, with the bivariate (or more generally, multivariate) cases
receiving mor... | 0 | 0 | 0 | 1 | 0 | 0 |
Finite Sample Analysis of Two-Timescale Stochastic Approximation with Applications to Reinforcement Learning | Two-timescale Stochastic Approximation (SA) algorithms are widely used in
Reinforcement Learning (RL). Their iterates have two parts that are updated
using distinct stepsizes. In this work, we develop a novel recipe for their
finite sample analysis. Using this, we provide a concentration bound, which is
the first suc... | 1 | 0 | 0 | 0 | 0 | 0 |
Existence and uniqueness of solutions to Y-systems and TBA equations | We consider Y-system functional equations of the form $$
Y_n(x+i)Y_n(x-i)=\prod_{m=1}^N (1+Y_m(x))^{G_{nm}}$$ and the corresponding
nonlinear integral equations of the Thermodynamic Bethe Ansatz. We prove an
existence and uniqueness result for solutions of these equations, subject to
appropriate conditions on the ana... | 0 | 1 | 0 | 0 | 0 | 0 |
Normalization of Neural Networks using Analytic Variance Propagation | We address the problem of estimating statistics of hidden units in a neural
network using a method of analytic moment propagation. These statistics are
useful for approximate whitening of the inputs in front of saturating
non-linearities such as a sigmoid function. This is important for
initialization of training and... | 0 | 0 | 0 | 1 | 0 | 0 |
Ferrimagnetism in the Spin-1/2 Heisenberg Antiferromagnet on a Distorted Triangular Lattice | The ground state of the spin-$1/2$ Heisenberg antiferromagnet on a distorted
triangular lattice is studied using a numerical-diagonalization method. The
network of interactions is the $\sqrt{3}\times\sqrt{3}$ type; the interactions
are continuously controlled between the undistorted triangular lattice and the
dice la... | 0 | 1 | 0 | 0 | 0 | 0 |
Delta sets for symmetric numerical semigroups with embedding dimension three | This work extends the results known for the Delta sets of non-symmetric
numerical semigroups with embedding dimension three to the symmetric case.
Thus, we have a fast algorithm to compute the Delta set of any embedding
dimension three numerical semigroup. Also, as a consequence of these resutls,
the sets that can be... | 0 | 0 | 1 | 0 | 0 | 0 |
Riemann-Hilbert problems for the resolved conifold | We study the Riemann-Hilbert problems associated to the Donaldson-Thomas
theory of the resolved conifold. We give explicit solutions in terms of the
Barnes double and triple sine functions. We show that the corresponding tau
function is a non-perturbative partition function, in the sense that its
asymptotic expansion... | 0 | 0 | 1 | 0 | 0 | 0 |
On the Power of Over-parametrization in Neural Networks with Quadratic Activation | We provide new theoretical insights on why over-parametrization is effective
in learning neural networks. For a $k$ hidden node shallow network with
quadratic activation and $n$ training data points, we show as long as $ k \ge
\sqrt{2n}$, over-parametrization enables local search algorithms to find a
\emph{globally} ... | 0 | 0 | 0 | 1 | 0 | 0 |
Multi-Label Learning with Label Enhancement | The task of multi-label learning is to predict a set of relevant labels for
the unseen instance. Traditional multi-label learning algorithms treat each
class label as a logical indicator of whether the corresponding label is
relevant or irrelevant to the instance, i.e., +1 represents relevant to the
instance and -1 r... | 1 | 0 | 0 | 0 | 0 | 0 |
Unsure When to Stop? Ask Your Semantic Neighbors | In iterative supervised learning algorithms it is common to reach a point in
the search where no further induction seems to be possible with the available
data. If the search is continued beyond this point, the risk of overfitting
increases significantly. Following the recent developments in inductive
semantic stocha... | 1 | 0 | 0 | 1 | 0 | 0 |
Deep Generative Learning via Variational Gradient Flow | We propose a general framework to learn deep generative models via
\textbf{V}ariational \textbf{Gr}adient Fl\textbf{ow} (VGrow) on probability
spaces. The evolving distribution that asymptotically converges to the target
distribution is governed by a vector field, which is the negative gradient of
the first variation... | 1 | 0 | 0 | 1 | 0 | 0 |
Warming trend in cold season of the Yangtze River Delta and its correlation with Siberian high | Based on the meteorological data from 1960 to 2010, we investigated the
temperature variation in the Yangtze River Delta (YRD) by using Mann-Kendall
nonparametric test and explored the correlation between the temperature in the
cold season and the Siberian high intensity (SHI) by using correlation analysis
method. Th... | 0 | 0 | 0 | 1 | 0 | 0 |
Modeling and Quantifying the Forces Driving Online Video Popularity Evolution | Video popularity is an essential reference for optimizing resource allocation
and video recommendation in online video services. However, there is still no
convincing model that can accurately depict a video's popularity evolution. In
this paper, we propose a dynamic popularity model by modeling the video
information... | 1 | 0 | 0 | 0 | 0 | 0 |
Multiagent Bidirectionally-Coordinated Nets: Emergence of Human-level Coordination in Learning to Play StarCraft Combat Games | Many artificial intelligence (AI) applications often require multiple
intelligent agents to work in a collaborative effort. Efficient learning for
intra-agent communication and coordination is an indispensable step towards
general AI. In this paper, we take StarCraft combat game as a case study, where
the task is to ... | 1 | 0 | 0 | 0 | 0 | 0 |
Measurement of the Lorentz-FitzGerald Body Contraction | A complete foundational discussion of acceleration in context of Special
Relativity is presented. Acceleration allows the measurement of a
Lorentz-FitzGerald body contraction created. It is argued that in the back
scattering of a probing laser beam from a relativistic flying electron cloud
mirror generated by an ultr... | 0 | 1 | 0 | 0 | 0 | 0 |
Information Directed Sampling for Stochastic Bandits with Graph Feedback | We consider stochastic multi-armed bandit problems with graph feedback, where
the decision maker is allowed to observe the neighboring actions of the chosen
action. We allow the graph structure to vary with time and consider both
deterministic and Erdős-Rényi random graph models. For such a graph
feedback model, we f... | 1 | 0 | 0 | 1 | 0 | 0 |
Multi-Evidence Filtering and Fusion for Multi-Label Classification, Object Detection and Semantic Segmentation Based on Weakly Supervised Learning | Supervised object detection and semantic segmentation require object or even
pixel level annotations. When there exist image level labels only, it is
challenging for weakly supervised algorithms to achieve accurate predictions.
The accuracy achieved by top weakly supervised algorithms is still
significantly lower tha... | 0 | 0 | 0 | 1 | 0 | 0 |
Hausdorff operators on holomorphic Hardy spaces and applications | The aim of this paper is to characterize the nonnegative functions $\varphi$
defined on $(0,\infty)$ for which the Hausdorff operator
$$\mathscr H_\varphi f(z)= \int_0^\infty
f\left(\frac{z}{t}\right)\frac{\varphi(t)}{t}dt$$ is bounded on the Hardy
spaces of the upper half-plane $\mathcal H_a^p(\mathbb C_+)$, $p\in[1... | 0 | 0 | 1 | 0 | 0 | 0 |
Three-dimensional color code thresholds via statistical-mechanical mapping | Three-dimensional (3D) color codes have advantages for fault-tolerant quantum
computing, such as protected quantum gates with relatively low overhead and
robustness against imperfect measurement of error syndromes. Here we
investigate the storage threshold error rates for bit-flip and phase-flip noise
in the 3D color... | 0 | 1 | 0 | 0 | 0 | 0 |
Does Your Phone Know Your Touch? | This paper explores supervised techniques for continuous anomaly detection
from biometric touch screen data. A capacitive sensor array used to mimic a
touch screen as used to collect touch and swipe gestures from participants. The
gestures are recorded over fixed segments of time, with position and force
measured for... | 0 | 0 | 0 | 1 | 0 | 0 |
Nucleus: A Pilot Project | Early in 2016, an environmental scan was conducted by the Research Library
Data Working Group for three purposes:
1.) Perform a survey of the data management landscape at Los Alamos National
Laboratory in order to identify local gaps in data management services.
2.) Conduct an environmental scan of external instituti... | 1 | 0 | 0 | 0 | 0 | 0 |
Non Volatile MoS$_{2}$ Field Effect Transistors Directly Gated By Single Crystalline Epitaxial Ferroelectric | We demonstrate non-volatile, n-type, back-gated, MoS$_{2}$ transistors,
placed directly on an epitaxial grown, single crystalline,
PbZr$_{0.2}$Ti$_{0.8}$O$_{3}$ (PZT) ferroelectric. The transistors show decent
ON current (19 ${\mu}A/{\mu}$m), high on-off ratio (10$^{7}$), and a
subthreshold swing of (SS ~ 92 mV/dec) ... | 0 | 1 | 0 | 0 | 0 | 0 |
Fast and Accurate Sparse Coding of Visual Stimuli with a Simple, Ultra-Low-Energy Spiking Architecture | Memristive crossbars have become a popular means for realizing unsupervised
and supervised learning techniques. In previous neuromorphic architectures with
leaky integrate-and-fire neurons, the crossbar itself has been separated from
the neuron capacitors to preserve mathematical rigor. In this work, we sought
to sim... | 1 | 0 | 0 | 0 | 0 | 0 |
Astronomy of Cholanaikkan tribe of Kerala | Cholanaikkans are a diminishing tribe of India. With a population of less
than 200 members, this tribe living in the reserved forests about 80 km from
Kozhikode, it is one of the most isolated tribes. A programme of the Government
of Kerala brings some of them to Kozhikode once a year. We studied various
aspects of t... | 0 | 1 | 0 | 0 | 0 | 0 |
Integral Equations and Machine Learning | As both light transport simulation and reinforcement learning are ruled by
the same Fredholm integral equation of the second kind, reinforcement learning
techniques may be used for photorealistic image synthesis: Efficiency may be
dramatically improved by guiding light transport paths by an approximate
solution of th... | 1 | 0 | 0 | 0 | 0 | 0 |
Experiments on bright field and dark field high energy electron imaging with thick target material | Using a high energy electron beam for the imaging of high density matter with
both high spatial-temporal and areal density resolution under extreme states of
temperature and pressure is one of the critical challenges in high energy
density physics . When a charged particle beam passes through an opaque target,
the be... | 0 | 1 | 0 | 0 | 0 | 0 |
A Non-linear Approach to Space Dimension Perception by a Naive Agent | Developmental Robotics offers a new approach to numerous AI features that are
often taken as granted. Traditionally, perception is supposed to be an inherent
capacity of the agent. Moreover, it largely relies on models built by the
system's designer. A new approach is to consider perception as an
experimentally acqui... | 1 | 0 | 0 | 0 | 0 | 0 |
Foolbox: A Python toolbox to benchmark the robustness of machine learning models | Even todays most advanced machine learning models are easily fooled by almost
imperceptible perturbations of their inputs. Foolbox is a new Python package to
generate such adversarial perturbations and to quantify and compare the
robustness of machine learning models. It is build around the idea that the
most compara... | 1 | 0 | 0 | 1 | 0 | 0 |
Two-dimensional boron on Pb (110) surface | We simulate boron on Pb(110) surface by using ab initio evolutionary
methodology. Interestingly, the two-dimensional (2D) Dirac Pmmn boron can be
formed because of good lattice matching. Unexpectedly, by increasing the
thickness of 2D boron, a three-bonded graphene-like structure (P2_1/c boron)
was revealed to posses... | 0 | 1 | 0 | 0 | 0 | 0 |
SOLAR: Deep Structured Latent Representations for Model-Based Reinforcement Learning | Model-based reinforcement learning (RL) methods can be broadly categorized as
global model methods, which depend on learning models that provide sensible
predictions in a wide range of states, or local model methods, which
iteratively refit simple models that are used for policy improvement. While
predicting future s... | 1 | 0 | 0 | 1 | 0 | 0 |
Robust and Fast Decoding of High-Capacity Color QR Codes for Mobile Applications | The use of color in QR codes brings extra data capacity, but also inflicts
tremendous challenges on the decoding process due to chromatic distortion,
cross-channel color interference and illumination variation. Particularly, we
further discover a new type of chromatic distortion in high-density color QR
codes, cross-... | 1 | 0 | 0 | 0 | 0 | 0 |
The quest for H$_3^+$ at Neptune: deep burn observations with NASA IRTF iSHELL | Emission from the molecular ion H$_3^+$ is a powerful diagnostic of the upper
atmosphere of Jupiter, Saturn, and Uranus, but it remains undetected at
Neptune. In search of this emission, we present near-infrared spectral
observations of Neptune between 3.93 and 4.00 $\mu$m taken with the newly
commissioned iSHELL ins... | 0 | 1 | 0 | 0 | 0 | 0 |
Unreasonable Effectivness of Deep Learning | We show how well known rules of back propagation arise from a weighted
combination of finite automata. By redefining a finite automata as a predictor
we combine the set of all $k$-state finite automata using a weighted majority
algorithm. This aggregated prediction algorithm can be simplified using
symmetry, and we p... | 0 | 0 | 0 | 1 | 0 | 0 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.