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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Composing Differential Privacy and Secure Computation: A case study on scaling private record linkage | Private record linkage (PRL) is the problem of identifying pairs of records
that are similar as per an input matching rule from databases held by two
parties that do not trust one another. We identify three key desiderata that a
PRL solution must ensure: 1) perfect precision and high recall of matching
pairs, 2) a pr... | 1 | 0 | 0 | 0 | 0 | 0 |
Recurrent Neural Filters: Learning Independent Bayesian Filtering Steps for Time Series Prediction | Despite the recent popularity of deep generative state space models, few
comparisons have been made between network architectures and the inference
steps of the Bayesian filtering framework -- with most models simultaneously
approximating both state transition and update steps with a single recurrent
neural network (... | 1 | 0 | 0 | 1 | 0 | 0 |
A Submodularity-Based Approach for Multi-Agent Optimal Coverage Problems | We consider the optimal coverage problem where a multi-agent network is
deployed in an environment with obstacles to maximize a joint event detection
probability. The objective function of this problem is non-convex and no global
optimum is guaranteed by gradient-based algorithms developed to date. We first
show that... | 1 | 0 | 1 | 0 | 0 | 0 |
A GPU-based Multi-level Algorithm for Boundary Value Problems | A novel and scalable geometric multi-level algorithm is presented for the
numerical solution of elliptic partial differential equations, specially
designed to run with high occupancy of streaming processors inside Graphics
Processing Units(GPUs). The algorithm consists of iterative, superposed
operations on a single ... | 1 | 1 | 0 | 0 | 0 | 0 |
Counterexample-Guided k-Induction Verification for Fast Bug Detection | Recently, the k-induction algorithm has proven to be a successful approach
for both finding bugs and proving correctness. However, since the algorithm is
an incremental approach, it might waste resources trying to prove incorrect
programs. In this paper, we propose to extend the k-induction algorithm in
order to shor... | 1 | 0 | 0 | 0 | 0 | 0 |
Cautious Model Predictive Control using Gaussian Process Regression | Gaussian process (GP) regression has been widely used in supervised machine
learning due to its flexibility and inherent ability to describe uncertainty in
function estimation. In the context of control, it is seeing increasing use for
modeling of nonlinear dynamical systems from data, as it allows the direct
assessm... | 1 | 0 | 1 | 0 | 0 | 0 |
Probabilistic Trajectory Segmentation by Means of Hierarchical Dirichlet Process Switching Linear Dynamical Systems | Using movement primitive libraries is an effective means to enable robots to
solve more complex tasks. In order to build these movement libraries, current
algorithms require a prior segmentation of the demonstration trajectories. A
promising approach is to model the trajectory as being generated by a set of
Switching... | 1 | 0 | 0 | 1 | 0 | 0 |
Radio Frequency Interference Mitigation | Radio astronomy observational facilities are under constant upgradation and
development to achieve better capabilities including increasing the time and
frequency resolutions of the recorded data, and increasing the receiving and
recording bandwidth. As only a limited spectrum resource has been allocated to
radio ast... | 0 | 1 | 0 | 0 | 0 | 0 |
Online Calibration of Phasor Measurement Unit Using Density-Based Spatial Clustering | Data quality of Phasor Measurement Unit (PMU) is receiving increasing
attention as it has been identified as one of the limiting factors that affect
many wide-area measurement system (WAMS) based applications. In general,
existing PMU calibration methods include offline testing and model based
approaches. However, in... | 1 | 0 | 0 | 0 | 0 | 0 |
Some basic properties of bounded solutions of parabolic equations with p-Laplacian diffusion | We provide a detailed (and fully rigorous) derivation of several fundamental
properties of bounded weak solutions to initial-value problems for general
conservative 2nd-order parabolic equations with p-Laplacian diffusion and
(arbitrary) bounded and integrable initial data.
| 0 | 0 | 1 | 0 | 0 | 0 |
Andreev Reflection without Fermi surface alignment in High T$_{c}$-Topological heterostructures | We address the controversy over the proximity effect between topological
materials and high T$_{c}$ superconductors. Junctions are produced between
Bi$_{2}$Sr$_{2}$CaCu$_{2}$O$_{8+\delta}$ and materials with different Fermi
surfaces (Bi$_{2}$Te$_{3}$ \& graphite). Both cases reveal tunneling spectra
consistent with A... | 0 | 1 | 0 | 0 | 0 | 0 |
Structural Data Recognition with Graph Model Boosting | This paper presents a novel method for structural data recognition using a
large number of graph models. In general, prevalent methods for structural data
recognition have two shortcomings: 1) Only a single model is used to capture
structural variation. 2) Naive recognition methods are used, such as the
nearest neigh... | 1 | 0 | 0 | 1 | 0 | 0 |
Exceptional points in two simple textbook examples | We propose to introduce the concept of exceptional points in intermediate
courses on mathematics and classical mechanics by means of simple textbook
examples. The first one is an ordinary second-order differential equation with
constant coefficients. The second one is the well known damped harmonic
oscillator. They e... | 0 | 1 | 0 | 0 | 0 | 0 |
Bootstrap of residual processes in regression: to smooth or not to smooth ? | In this paper we consider a location model of the form $Y = m(X) +
\varepsilon$, where $m(\cdot)$ is the unknown regression function, the error
$\varepsilon$ is independent of the $p$-dimensional covariate $X$ and
$E(\varepsilon)=0$. Given i.i.d. data $(X_1,Y_1),\ldots,(X_n,Y_n)$ and given an
estimator $\hat m(\cdot)... | 0 | 0 | 1 | 1 | 0 | 0 |
Polynomiality for the Poisson centre of truncated maximal parabolic subalgebras | We show that the Poisson centre of truncated maximal parabolic subalgebras of
a simple Lie algebra of type B, D and E_6 is a polynomial algebra.
In roughly half of the cases the polynomiality of the Poisson centre was
already known by a completely different method.
For the rest of the cases, our approach is to constr... | 0 | 0 | 1 | 0 | 0 | 0 |
Row-Centric Lossless Compression of Markov Images | Motivated by the question of whether the recently introduced Reduced Cutset
Coding (RCC) offers rate-complexity performance benefits over conventional
context-based conditional coding for sources with two-dimensional Markov
structure, this paper compares several row-centric coding strategies that vary
in the amount o... | 1 | 0 | 0 | 0 | 0 | 0 |
Planetesimal formation by the streaming instability in a photoevaporating disk | Recent years have seen growing interest in the streaming instability as a
candidate mechanism to produce planetesimals. However, these investigations
have been limited to small-scale simulations. We now present the results of a
global protoplanetary disk evolution model that incorporates planetesimal
formation by the... | 0 | 1 | 0 | 0 | 0 | 0 |
Fault Tolerant Thermal Control of Steam Turbine Shell Deflections | The metal-to-metal clearances of a steam turbine during full or part load
operation are among the main drivers of efficiency. The requirement to add
clearances is driven by a number of factors including the relative movements of
the steam turbine shell and rotor during transient conditions such as startup
and shutdow... | 1 | 0 | 0 | 0 | 0 | 0 |
Causal Mediation Analysis Leveraging Multiple Types of Summary Statistics Data | Summary statistics of genome-wide association studies (GWAS) teach causal
relationship between millions of genetic markers and tens and thousands of
phenotypes. However, underlying biological mechanisms are yet to be elucidated.
We can achieve necessary interpretation of GWAS in a causal mediation
framework, looking ... | 1 | 0 | 0 | 1 | 1 | 0 |
Causal Queries from Observational Data in Biological Systems via Bayesian Networks: An Empirical Study in Small Networks | Biological networks are a very convenient modelling and visualisation tool to
discover knowledge from modern high-throughput genomics and postgenomics data
sets. Indeed, biological entities are not isolated, but are components of
complex multi-level systems. We go one step further and advocate for the
consideration o... | 0 | 0 | 0 | 1 | 1 | 0 |
Hierarchical Bloom Filter Trees for Approximate Matching | Bytewise approximate matching algorithms have in recent years shown
significant promise in de- tecting files that are similar at the byte level.
This is very useful for digital forensic investigators, who are regularly faced
with the problem of searching through a seized device for pertinent data. A
common scenario i... | 1 | 0 | 0 | 0 | 0 | 0 |
GANDALF - Graphical Astrophysics code for N-body Dynamics And Lagrangian Fluids | GANDALF is a new hydrodynamics and N-body dynamics code designed for
investigating planet formation, star formation and star cluster problems.
GANDALF is written in C++, parallelised with both OpenMP and MPI and contains a
python library for analysis and visualisation. The code has been written with a
fully object-or... | 0 | 1 | 0 | 0 | 0 | 0 |
Pre-freezing transition in Boltzmann-Gibbs measures associated with log-correlated fields | We consider Boltzmann-Gibbs measures associated with log-correlated Gaussian
fields as potentials and study their multifractal properties which exhibit
phase transitions. In particular, the pre-freezing and freezing phenomena of
the annealed exponent, predicted by Fyodorov using a modified
replica-symmetry-breaking a... | 0 | 1 | 0 | 0 | 0 | 0 |
Learning Combinatorial Optimization Algorithms over Graphs | The design of good heuristics or approximation algorithms for NP-hard
combinatorial optimization problems often requires significant specialized
knowledge and trial-and-error. Can we automate this challenging, tedious
process, and learn the algorithms instead? In many real-world applications, it
is typically the case... | 1 | 0 | 0 | 1 | 0 | 0 |
Optimal Oil Production and Taxation in Presence of Global Disruptions | This paper studies the optimal extraction policy of an oil field as well as
the efficient taxation of the revenues generated. Taking into account the fact
that the oil price in worldwide commodity markets fluctuates randomly following
global and seasonal macroeconomic parameters, we model the evolution of the oil
pri... | 0 | 0 | 1 | 0 | 0 | 0 |
Critical well-posedness and scattering results for fractional Hartree-type equations | Scattering for the mass-critical fractional Schrödinger equation with a
cubic Hartree-type nonlinearity for initial data in a small ball in the
scale-invariant space of three-dimensional radial and square-integrable initial
data is established. For this, we prove a bilinear estimate for free solutions
and extend it t... | 0 | 0 | 1 | 0 | 0 | 0 |
Lightweight Multilingual Software Analysis | Developer preferences, language capabilities and the persistence of older
languages contribute to the trend that large software codebases are often
multilingual, that is, written in more than one computer language. While
developers can leverage monolingual software development tools to build
software components, comp... | 1 | 0 | 0 | 0 | 0 | 0 |
Room-temperature 1.54 $μ$m photoluminescence of Er:O$_x$ centers at extremely low concentration in silicon | The demand for single photon sources at $\lambda~=~1.54~\mu$m, which follows
from the consistent development of quantum networks based on commercial optical
fibers, makes Er:O$_x$ centers in Si still a viable resource thanks to the
optical transition of $Er^{3+}~:~^4I_{13/2}~\rightarrow~^4I_{15/2}$. Yet, to
date, the... | 0 | 1 | 0 | 0 | 0 | 0 |
Sparse Algorithm for Robust LSSVM in Primal Space | As enjoying the closed form solution, least squares support vector machine
(LSSVM) has been widely used for classification and regression problems having
the comparable performance with other types of SVMs. However, LSSVM has two
drawbacks: sensitive to outliers and lacking sparseness. Robust LSSVM (R-LSSVM)
overcome... | 1 | 0 | 0 | 1 | 0 | 0 |
Value Propagation for Decentralized Networked Deep Multi-agent Reinforcement Learning | We consider the networked multi-agent reinforcement learning (MARL) problem
in a fully decentralized setting, where agents learn to coordinate to achieve
the joint success. This problem is widely encountered in many areas including
traffic control, distributed control, and smart grids. We assume that the
reward funct... | 1 | 0 | 0 | 1 | 0 | 0 |
Collect at Once, Use Effectively: Making Non-interactive Locally Private Learning Possible | Non-interactive Local Differential Privacy (LDP) requires data analysts to
collect data from users through noisy channel at once. In this paper, we extend
the frontiers of Non-interactive LDP learning and estimation from several
aspects. For learning with smooth generalized linear losses, we propose an
approximate st... | 1 | 0 | 0 | 0 | 0 | 0 |
Learning Independent Causal Mechanisms | Statistical learning relies upon data sampled from a distribution, and we
usually do not care what actually generated it in the first place. From the
point of view of causal modeling, the structure of each distribution is induced
by physical mechanisms that give rise to dependences between observables.
Mechanisms, ho... | 1 | 0 | 0 | 1 | 0 | 0 |
A Bayesian Model for False Information Belief Impact, Optimal Design, and Fake News Containment | This work is a technical approach to modeling false information nature,
design, belief impact and containment in multi-agent networks. We present a
Bayesian mathematical model for source information and viewer's belief, and how
the former impacts the latter in a media (network) of broadcasters and viewers.
Given the ... | 1 | 0 | 0 | 0 | 0 | 0 |
Topological dynamics of gyroscopic and Floquet lattices from Newton's laws | Despite intense interest in realizing topological phases across a variety of
electronic, photonic and mechanical platforms, the detailed microscopic origin
of topological behavior often remains elusive. To bridge this conceptual gap,
we show how hallmarks of topological modes - boundary localization and
chirality - e... | 0 | 1 | 1 | 0 | 0 | 0 |
Stability of axisymmetric chiral skyrmions | We examine topological solitons in a minimal variational model for a chiral
magnet, so-called chiral skyrmions. In the regime of large background fields,
we prove linear stability of axisymmetric chiral skyrmions under arbitrary
perturbations in the energy space, a long-standing open question in physics
literature. M... | 0 | 0 | 1 | 0 | 0 | 0 |
Efficiency versus instability in plasma accelerators | Plasma wake-field acceleration is one of the main technologies being
developed for future high-energy colliders. Potentially, it can create a
cost-effective path to the highest possible energies for e+e- or
{\gamma}-{\gamma} colliders and produce a profound effect on the developments
for high-energy physics. Accelera... | 0 | 1 | 0 | 0 | 0 | 0 |
Resistivity bound for hydrodynamic bad metals | We obtain a rigorous upper bound on the resistivity $\rho$ of an electron
fluid whose electronic mean free path is short compared to the scale of spatial
inhomogeneities. When such a hydrodynamic electron fluid supports a non-thermal
diffusion process -- such as an imbalance mode between different bands -- we
show th... | 0 | 1 | 0 | 0 | 0 | 0 |
Minimal Exploration in Structured Stochastic Bandits | This paper introduces and addresses a wide class of stochastic bandit
problems where the function mapping the arm to the corresponding reward
exhibits some known structural properties. Most existing structures (e.g.
linear, Lipschitz, unimodal, combinatorial, dueling, ...) are covered by our
framework. We derive an a... | 1 | 0 | 0 | 1 | 0 | 0 |
Data Driven Exploratory Attacks on Black Box Classifiers in Adversarial Domains | While modern day web applications aim to create impact at the civilization
level, they have become vulnerable to adversarial activity, where the next
cyber-attack can take any shape and can originate from anywhere. The increasing
scale and sophistication of attacks, has prompted the need for a data driven
solution, w... | 1 | 0 | 0 | 1 | 0 | 0 |
On Optimistic versus Randomized Exploration in Reinforcement Learning | We discuss the relative merits of optimistic and randomized approaches to
exploration in reinforcement learning. Optimistic approaches presented in the
literature apply an optimistic boost to the value estimate at each state-action
pair and select actions that are greedy with respect to the resulting
optimistic value... | 1 | 0 | 0 | 1 | 0 | 0 |
Fast Monte-Carlo Localization on Aerial Vehicles using Approximate Continuous Belief Representations | Size, weight, and power constrained platforms impose constraints on
computational resources that introduce unique challenges in implementing
localization algorithms. We present a framework to perform fast localization on
such platforms enabled by the compressive capabilities of Gaussian Mixture
Model representations ... | 1 | 0 | 0 | 0 | 0 | 0 |
Generalized two-field $α$-attractor models from geometrically finite hyperbolic surfaces | We consider four-dimensional gravity coupled to a non-linear sigma model
whose scalar manifold is a non-compact geometrically finite surface $\Sigma$
endowed with a Riemannian metric of constant negative curvature. When the
space-time is an FLRW universe, such theories produce a very wide
generalization of two-field ... | 0 | 1 | 1 | 0 | 0 | 0 |
The Geodetic Hull Number is Hard for Chordal Graphs | We show the hardness of the geodetic hull number for chordal graphs.
| 1 | 0 | 0 | 0 | 0 | 0 |
$\overline{M}_{1,n}$ is usually not uniruled in characteristic $p$ | Using etale cohomology, we define a birational invariant for varieties in
characteristic $p$ that serves as an obstruction to uniruledness - a variant on
an obstruction to unirationality due to Ekedahl. We apply this to
$\overline{M}_{1,n}$ and show that $\overline{M}_{1,n}$ is not uniruled in
characteristic $p$ as l... | 0 | 0 | 1 | 0 | 0 | 0 |
Active Community Detection: A Maximum Likelihood Approach | We propose novel semi-supervised and active learning algorithms for the
problem of community detection on networks. The algorithms are based on
optimizing the likelihood function of the community assignments given a graph
and an estimate of the statistical model that generated it. The optimization
framework is inspir... | 1 | 0 | 0 | 1 | 0 | 0 |
Continuum Limit of Posteriors in Graph Bayesian Inverse Problems | We consider the problem of recovering a function input of a differential
equation formulated on an unknown domain $M$. We assume to have access to a
discrete domain $M_n=\{x_1, \dots, x_n\} \subset M$, and to noisy measurements
of the output solution at $p\le n$ of those points. We introduce a graph-based
Bayesian in... | 0 | 0 | 1 | 1 | 0 | 0 |
Automatic Conflict Detection in Police Body-Worn Audio | Automatic conflict detection has grown in relevance with the advent of
body-worn technology, but existing metrics such as turn-taking and overlap are
poor indicators of conflict in police-public interactions. Moreover, standard
techniques to compute them fall short when applied to such diversified and
noisy contexts.... | 1 | 0 | 0 | 1 | 0 | 0 |
The cobordism hypothesis | Assuming a conjecture about factorization homology with adjoints, we prove
the cobordism hypothesis, after Baez-Dolan, Costello, Hopkins-Lurie, and Lurie.
| 0 | 0 | 1 | 0 | 0 | 0 |
LAMOST telescope reveals that Neptunian cousins of hot Jupiters are mostly single offspring of stars that are rich in heavy elements | We discover a population of short-period, Neptune-size planets sharing key
similarities with hot Jupiters: both populations are preferentially hosted by
metal-rich stars, and both are preferentially found in Kepler systems with
single transiting planets. We use accurate LAMOST DR4 stellar parameters for
main-sequence... | 0 | 1 | 0 | 0 | 0 | 0 |
A Latent Variable Model for Two-Dimensional Canonical Correlation Analysis and its Variational Inference | Describing the dimension reduction (DR) techniques by means of probabilistic
models has recently been given special attention. Probabilistic models, in
addition to a better interpretability of the DR methods, provide a framework
for further extensions of such algorithms. One of the new approaches to the
probabilistic... | 1 | 0 | 0 | 1 | 0 | 0 |
Model enumeration in propositional circumscription via unsatisfiable core analysis | Many practical problems are characterized by a preference relation over
admissible solutions, where preferred solutions are minimal in some sense. For
example, a preferred diagnosis usually comprises a minimal set of reasons that
is sufficient to cause the observed anomaly. Alternatively, a minimal
correction subset ... | 1 | 0 | 0 | 0 | 0 | 0 |
Structured Neural Summarization | Summarization of long sequences into a concise statement is a core problem in
natural language processing, requiring non-trivial understanding of the input.
Based on the promising results of graph neural networks on highly structured
data, we develop a framework to extend existing sequence encoders with a graph
compo... | 1 | 0 | 0 | 0 | 0 | 0 |
Variations on a Visserian Theme | A first order theory T is said to be "tight" if for any two deductively
closed extensions U and V of T (both of which are formulated in the language of
T), U and V are bi-interpretable iff U = V. By a theorem of Visser, PA (Peano
Arithmetic) is tight. Here we show that Z_2 (second order arithmetic), ZF
(Zermelo-Fraen... | 0 | 0 | 1 | 0 | 0 | 0 |
Galerkin Least-Squares Stabilization in Ice Sheet Modeling - Accuracy, Robustness, and Comparison to other Techniques | We investigate the accuracy and robustness of one of the most common methods
used in glaciology for the discretization of the $\mathfrak{p}$-Stokes
equations: equal order finite elements with Galerkin Least-Squares (GLS)
stabilization. Furthermore we compare the results to other stabilized methods.
We find that the v... | 0 | 1 | 0 | 0 | 0 | 0 |
Improved Query Reformulation for Concept Location using CodeRank and Document Structures | During software maintenance, developers usually deal with a significant
number of software change requests. As a part of this, they often formulate an
initial query from the request texts, and then attempt to map the concepts
discussed in the request to relevant source code locations in the software
system (a.k.a., c... | 1 | 0 | 0 | 0 | 0 | 0 |
High-performance parallel computing in the classroom using the public goods game as an example | The use of computers in statistical physics is common because the sheer
number of equations that describe the behavior of an entire system particle by
particle often makes it impossible to solve them exactly. Monte Carlo methods
form a particularly important class of numerical methods for solving problems
in statisti... | 0 | 1 | 0 | 0 | 0 | 0 |
Coupled spin-charge dynamics in helical Fermi liquids beyond the random phase approximation | We consider a helical system of fermions with a generic spin (or pseudospin)
orbit coupling. Using the equation of motion approach for the single-particle
distribution functions, and a mean-field decoupling of the higher order
distribution functions, we find a closed form for the charge and spin density
fluctuations ... | 0 | 1 | 0 | 0 | 0 | 0 |
Correlation decay in fermionic lattice systems with power-law interactions at non-zero temperature | We study correlations in fermionic lattice systems with long-range
interactions in thermal equilibrium. We prove a bound on the correlation decay
between anti-commuting operators and generalize a long-range Lieb-Robinson type
bound. Our results show that in these systems of spatial dimension $D$ with,
not necessarily... | 0 | 1 | 0 | 0 | 0 | 0 |
Integrated Microsimulation Framework for Dynamic Pedestrian Movement Estimation in Mobility Hub | We present an integrated microsimulation framework to estimate the pedestrian
movement over time and space with limited data on directional counts. Using the
activity-based approach, simulation can compute the overall demand and
trajectory of each agent, which are in accordance with the available partial
observations... | 0 | 1 | 1 | 0 | 0 | 0 |
Dimensionality Reduction for Stationary Time Series via Stochastic Nonconvex Optimization | Stochastic optimization naturally arises in machine learning. Efficient
algorithms with provable guarantees, however, are still largely missing, when
the objective function is nonconvex and the data points are dependent. This
paper studies this fundamental challenge through a streaming PCA problem for
stationary time... | 0 | 0 | 0 | 1 | 0 | 0 |
Efficient tracking of a growing number of experts | We consider a variation on the problem of prediction with expert advice,
where new forecasters that were unknown until then may appear at each round. As
often in prediction with expert advice, designing an algorithm that achieves
near-optimal regret guarantees is straightforward, using aggregation of
experts. However... | 1 | 0 | 0 | 1 | 0 | 0 |
Toeplitz Inverse Covariance-Based Clustering of Multivariate Time Series Data | Subsequence clustering of multivariate time series is a useful tool for
discovering repeated patterns in temporal data. Once these patterns have been
discovered, seemingly complicated datasets can be interpreted as a temporal
sequence of only a small number of states, or clusters. For example, raw sensor
data from a ... | 1 | 0 | 1 | 0 | 0 | 0 |
The ellipse law: Kirchhoff meets dislocations | In this paper we consider a nonlocal energy $I_\alpha$ whose kernel is
obtained by adding to the Coulomb potential an anisotropic term weighted by a
parameter $\alpha\in \R$. The case $\alpha=0$ corresponds to purely logarithmic
interactions, minimised by the celebrated circle law for a quadratic
confinement; $\alpha... | 0 | 0 | 1 | 0 | 0 | 0 |
SAML-QC: a Stochastic Assessment and Machine Learning based QC technique for Industrial Printing | Recently, the advancement in industrial automation and high-speed printing
has raised numerous challenges related to the printing quality inspection of
final products. This paper proposes a machine vision based technique to assess
the printing quality of text on industrial objects. The assessment is based on
three qu... | 1 | 0 | 0 | 0 | 0 | 0 |
Probing the gravitational redshift with an Earth-orbiting satellite | We present an approach to testing the gravitational redshift effect using the
RadioAstron satellite. The experiment is based on a modification of the Gravity
Probe A scheme of nonrelativistic Doppler compensation and benefits from the
highly eccentric orbit and ultra-stable atomic hydrogen maser frequency
standard of... | 0 | 1 | 0 | 0 | 0 | 0 |
A stencil scaling approach for accelerating matrix-free finite element implementations | We present a novel approach to fast on-the-fly low order finite element
assembly for scalar elliptic partial differential equations of Darcy type with
variable coefficients optimized for matrix-free implementations. Our approach
introduces a new operator that is obtained by appropriately scaling the
reference stiffne... | 1 | 0 | 0 | 0 | 0 | 0 |
Cramér-Rao Lower Bounds for Positioning with Large Intelligent Surfaces | We consider the potential for positioning with a system where antenna arrays
are deployed as a large intelligent surface (LIS). We derive
Fisher-informations and Cramér-Rao lower bounds (CRLB) in closed-form for
terminals along the central perpendicular line (CPL) of the LIS for all three
Cartesian dimensions. For te... | 1 | 0 | 0 | 0 | 0 | 0 |
Asymptotic behaviour methods for the Heat Equation. Convergence to the Gaussian | In this expository work we discuss the asymptotic behaviour of the solutions
of the classical heat equation posed in the whole Euclidean space.
After an introductory review of the main facts on the existence and
properties of solutions, we proceed with the proofs of convergence to the
Gaussian fundamental solution, a... | 0 | 0 | 1 | 0 | 0 | 0 |
Magnetization dynamics of weakly interacting sub-100 nm square artificial spin ices | Artificial Spin Ice (ASI), consisting of a two dimensional array of nanoscale
magnetic elements, provides a fascinating opportunity to observe the physics of
out of equilibrium systems. Initial studies concentrated on the static, frozen
state, whilst more recent studies have accessed the out-of-equilibrium dynamic,
f... | 0 | 1 | 0 | 0 | 0 | 0 |
Filtering Tweets for Social Unrest | Since the events of the Arab Spring, there has been increased interest in
using social media to anticipate social unrest. While efforts have been made
toward automated unrest prediction, we focus on filtering the vast volume of
tweets to identify tweets relevant to unrest, which can be provided to
downstream users fo... | 1 | 0 | 0 | 1 | 0 | 0 |
Structured Connectivity Augmentation | We initiate the algorithmic study of the following "structured augmentation"
question: is it possible to increase the connectivity of a given graph G by
superposing it with another given graph H? More precisely, graph F is the
superposition of G and H with respect to injective mapping \phi: V(H)->V(G) if
every edge u... | 1 | 0 | 0 | 0 | 0 | 0 |
Transition probability of Brownian motion in the octant and its application to default modeling | We derive a semi-analytic formula for the transition probability of
three-dimensional Brownian motion in the positive octant with absorption at the
boundaries. Separation of variables in spherical coordinates leads to an
eigenvalue problem for the resulting boundary value problem in the two angular
components. The ma... | 0 | 0 | 0 | 0 | 0 | 1 |
Block-Sparse Recurrent Neural Networks | Recurrent Neural Networks (RNNs) are used in state-of-the-art models in
domains such as speech recognition, machine translation, and language
modelling. Sparsity is a technique to reduce compute and memory requirements of
deep learning models. Sparse RNNs are easier to deploy on devices and high-end
server processors... | 1 | 0 | 0 | 1 | 0 | 0 |
Equitable neighbour-sum-distinguishing edge and total colourings | With any (not necessarily proper) edge $k$-colouring
$\gamma:E(G)\longrightarrow\{1,\dots,k\}$ of a graph $G$,one can associate a
vertex colouring $\sigma\_{\gamma}$ given by $\sigma\_{\gamma}(v)=\sum\_{e\ni
v}\gamma(e)$.A neighbour-sum-distinguishing edge $k$-colouring is an edge
colouring whose associated vertex co... | 1 | 0 | 1 | 0 | 0 | 0 |
An Oracle Property of The Nadaraya-Watson Kernel Estimator for High Dimensional Nonparametric Regression | The celebrated Nadaraya-Watson kernel estimator is among the most studied
method for nonparametric regression. A classical result is that its rate of
convergence depends on the number of covariates and deteriorates quickly as the
dimension grows, which underscores the "curse of dimensionality" and has
limited its use... | 0 | 0 | 1 | 1 | 0 | 0 |
Fast Rates for Bandit Optimization with Upper-Confidence Frank-Wolfe | We consider the problem of bandit optimization, inspired by stochastic
optimization and online learning problems with bandit feedback. In this
problem, the objective is to minimize a global loss function of all the
actions, not necessarily a cumulative loss. This framework allows us to study a
very general class of p... | 0 | 0 | 1 | 1 | 0 | 0 |
Highly sensitive atomic based MW interferometry | We theoretically study a scheme to develop an atomic based MW interferometry
using the Rydberg states in Rb. Unlike the traditional MW interferometry, this
scheme is not based upon the electrical circuits, hence the sensitivity of the
phase and the amplitude/strength of the MW field is not limited by the Nyquist
ther... | 0 | 1 | 0 | 0 | 0 | 0 |
The Wisdom of a Kalman Crowd | The Kalman Filter has been called one of the greatest inventions in
statistics during the 20th century. Its purpose is to measure the state of a
system by processing the noisy data received from different electronic sensors.
In comparison, a useful resource for managers in their effort to make the right
decisions is ... | 0 | 0 | 0 | 0 | 0 | 1 |
Noisy independent component analysis of auto-correlated components | We present a new method for the separation of superimposed, independent,
auto-correlated components from noisy multi-channel measurement. The presented
method simultaneously reconstructs and separates the components, taking all
channels into account and thereby increases the effective signal-to-noise ratio
considerab... | 0 | 1 | 0 | 1 | 0 | 0 |
Ages and structural and dynamical parameters of two globular clusters in the M81 group | GC-1 and GC-2 are two globular clusters (GCs) in the remote halo of M81 and
M82 in the M81 group discovered by Jang et al. using the {\it Hubble Space
Telescope} ({\it HST}) images. These two GCs were observed as part of the
Beijing--Arizona--Taiwan--Connecticut (BATC) Multicolor Sky Survey, using 14
intermediate-ban... | 0 | 1 | 0 | 0 | 0 | 0 |
Bayesian Renewables Scenario Generation via Deep Generative Networks | We present a method to generate renewable scenarios using Bayesian
probabilities by implementing the Bayesian generative adversarial
network~(Bayesian GAN), which is a variant of generative adversarial networks
based on two interconnected deep neural networks. By using a Bayesian
formulation, generators can be constr... | 0 | 0 | 0 | 1 | 0 | 0 |
Graphons: A Nonparametric Method to Model, Estimate, and Design Algorithms for Massive Networks | Many social and economic systems are naturally represented as networks, from
off-line and on-line social networks, to bipartite networks, like Netflix and
Amazon, between consumers and products. Graphons, developed as limits of
graphs, form a natural, nonparametric method to describe and estimate large
networks like ... | 1 | 1 | 0 | 0 | 0 | 0 |
Hopf Parametric Adjoint Objects through a 2-adjunction of the type Adj-Mnd | In this article Hopf parametric adjunctions are defined and analysed within
the context of the 2-adjunction of the type $\mathbf{Adj}$-$\mathbf{Mnd}$. In
order to do so, the definition of adjoint objects in the 2-category of
adjunctions and in the 2-category of monads for $Cat$ are revised and
characterized. This art... | 0 | 0 | 1 | 0 | 0 | 0 |
Krylov Subspace Recycling for Fast Iterative Least-Squares in Machine Learning | Solving symmetric positive definite linear problems is a fundamental
computational task in machine learning. The exact solution, famously, is
cubicly expensive in the size of the matrix. To alleviate this problem, several
linear-time approximations, such as spectral and inducing-point methods, have
been suggested and... | 1 | 0 | 0 | 1 | 0 | 0 |
Towards a Physical Oracle for the Partition Problem using Analogue Computing | Despite remarkable achievements in its practical tractability, the notorious
class of NP-complete problems has been escaping all attempts to find a
worst-case polynomial time-bound solution algorithms for any of them. The vast
majority of work relies on Turing machines or equivalent models, all of which
relate to dig... | 1 | 0 | 0 | 0 | 0 | 0 |
Bayesian Methods in Cosmology | These notes aim at presenting an overview of Bayesian statistics, the
underlying concepts and application methodology that will be useful to
astronomers seeking to analyse and interpret a wide variety of data about the
Universe. The level starts from elementary notions, without assuming any
previous knowledge of stat... | 0 | 1 | 0 | 1 | 0 | 0 |
Information Extraction in Illicit Domains | Extracting useful entities and attribute values from illicit domains such as
human trafficking is a challenging problem with the potential for widespread
social impact. Such domains employ atypical language models, have `long tails'
and suffer from the problem of concept drift. In this paper, we propose a
lightweight... | 1 | 0 | 0 | 0 | 0 | 0 |
A Tutorial on Kernel Density Estimation and Recent Advances | This tutorial provides a gentle introduction to kernel density estimation
(KDE) and recent advances regarding confidence bands and geometric/topological
features. We begin with a discussion of basic properties of KDE: the
convergence rate under various metrics, density derivative estimation, and
bandwidth selection. ... | 0 | 0 | 0 | 1 | 0 | 0 |
Optimizing expected word error rate via sampling for speech recognition | State-level minimum Bayes risk (sMBR) training has become the de facto
standard for sequence-level training of speech recognition acoustic models. It
has an elegant formulation using the expectation semiring, and gives large
improvements in word error rate (WER) over models trained solely using
cross-entropy (CE) or ... | 1 | 0 | 0 | 1 | 0 | 0 |
Real-Time Illegal Parking Detection System Based on Deep Learning | The increasing illegal parking has become more and more serious. Nowadays the
methods of detecting illegally parked vehicles are based on background
segmentation. However, this method is weakly robust and sensitive to
environment. Benefitting from deep learning, this paper proposes a novel
illegal vehicle parking det... | 1 | 0 | 0 | 1 | 0 | 0 |
On a representation of fractional Brownian motion and the limit distributions of statistics arising in cusp statistical models | We discuss some extensions of results from the recent paper by Chernoyarov et
al. (Ann. Inst. Stat. Math., October 2016) concerning limit distributions of
Bayesian and maximum likelihood estimators in the model "signal plus white
noise" with irregular cusp-type signals. Using a new representation of
fractional Browni... | 0 | 0 | 1 | 1 | 0 | 0 |
Stochastic Canonical Correlation Analysis | We tightly analyze the sample complexity of CCA, provide a learning algorithm
that achieves optimal statistical performance in time linear in the required
number of samples (up to log factors), as well as a streaming algorithm with
similar guarantees.
| 1 | 0 | 0 | 1 | 0 | 0 |
Segmentation of Instances by Hashing | We propose a novel approach to address the Simultaneous Detection and
Segmentation problem. Using hierarchical structures we use an efficient and
accurate procedure that exploits the hierarchy feature information using
Locality Sensitive Hashing. We build on recent work that utilizes convolutional
neural networks to ... | 1 | 0 | 0 | 0 | 0 | 0 |
Grafting for Combinatorial Boolean Model using Frequent Itemset Mining | This paper introduces the combinatorial Boolean model (CBM), which is defined
as the class of linear combinations of conjunctions of Boolean attributes. This
paper addresses the issue of learning CBM from labeled data. CBM is of high
knowledge interpretability but naïve learning of it requires exponentially
large com... | 1 | 0 | 0 | 1 | 0 | 0 |
Rapid Assessment of Damaged Homes in the Florida Keys after Hurricane Irma | On September 10, 2017, Hurricane Irma made landfall in the Florida Keys and
caused significant damage. Informed by hydrodynamic storm surge and wave
modeling and post-storm satellite imagery, a rapid damage survey was soon
conducted for 1600+ residential buildings in Big Pine Key and Marathon. Damage
categorizations ... | 0 | 0 | 0 | 1 | 0 | 0 |
Status maximization as a source of fairness in a networked dictator game | Human behavioural patterns exhibit selfish or competitive, as well as
selfless or altruistic tendencies, both of which have demonstrable effects on
human social and economic activity. In behavioural economics, such effects have
traditionally been illustrated experimentally via simple games like the
dictator and ultim... | 1 | 0 | 0 | 0 | 0 | 1 |
On Dziobek Special Central Configurations | We study the special central configurations of the curved N-body problem in
S^3. We show that there are special central configurations formed by N masses
for any N >2. We then extend the concept of special central configurations to
S^n, n>0, and study one interesting class of special central configurations in
S^n, th... | 0 | 0 | 1 | 0 | 0 | 0 |
Laser Interferometer Space Antenna | Following the selection of The Gravitational Universe by ESA, and the
successful flight of LISA Pathfinder, the LISA Consortium now proposes a 4 year
mission in response to ESA's call for missions for L3. The observatory will be
based on three arms with six active laser links, between three identical
spacecraft in a ... | 0 | 1 | 0 | 0 | 0 | 0 |
Learning from a lot: Empirical Bayes in high-dimensional prediction settings | Empirical Bayes is a versatile approach to `learn from a lot' in two ways:
first, from a large number of variables and second, from a potentially large
amount of prior information, e.g. stored in public repositories. We review
applications of a variety of empirical Bayes methods to several well-known
model-based pred... | 0 | 0 | 0 | 1 | 0 | 0 |
Dissipativity Theory for Accelerating Stochastic Variance Reduction: A Unified Analysis of SVRG and Katyusha Using Semidefinite Programs | Techniques for reducing the variance of gradient estimates used in stochastic
programming algorithms for convex finite-sum problems have received a great
deal of attention in recent years. By leveraging dissipativity theory from
control, we provide a new perspective on two important variance-reduction
algorithms: SVR... | 0 | 0 | 0 | 1 | 0 | 0 |
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