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
Statistical Latent Space Approach for Mixed Data Modelling and Applications
The analysis of mixed data has been raising challenges in statistics and machine learning. One of two most prominent challenges is to develop new statistical techniques and methodologies to effectively handle mixed data by making the data less heterogeneous with minimum loss of information. The other challenge is tha...
1
0
0
1
0
0
Near-field coupling of gold plasmonic antennas for sub-100 nm magneto-thermal microscopy
The development of spintronic technology with increasingly dense, high-speed, and complex devices will be accelerated by accessible microscopy techniques capable of probing magnetic phenomena on picosecond time scales and at deeply sub-micron length scales. A recently developed time-resolved magneto-thermal microscop...
0
1
0
0
0
0
A reproducible effect size is more useful than an irreproducible hypothesis test to analyze high throughput sequencing datasets
Motivation: P values derived from the null hypothesis significance testing framework are strongly affected by sample size, and are known to be irreproducible in underpowered studies, yet no suitable replacement has been proposed. Results: Here we present implementations of non-parametric standardized median effect si...
0
0
0
0
1
0
High temperature thermodynamics of the honeycomb-lattice Kitaev-Heisenberg model: A high temperature series expansion study
We develop high temperature series expansions for the thermodynamic properties of the honeycomb-lattice Kitaev-Heisenberg model. Numerical results for uniform susceptibility, heat capacity and entropy as a function of temperature for different values of the Kitaev coupling $K$ and Heisenberg exachange coupling $J$ (w...
0
1
0
0
0
0
Laplace Beltrami operator in the Baran metric and pluripotential equilibrium measure: the ball, the simplex and the sphere
The Baran metric $\delta_E$ is a Finsler metric on the interior of $E\subset \R^n$ arising from Pluripotential Theory. We consider the few instances, namely $E$ being the ball, the simplex, or the sphere, where $\delta_E$ is known to be Riemaniann and we prove that the eigenfunctions of the associated Laplace Beltram...
0
0
1
0
0
0
Magnetic polarons in a nonequilibrium polariton condensate
We consider a condensate of exciton-polaritons in a diluted magnetic semiconductor microcavity. Such system may exhibit magnetic self-trapping in the case of sufficiently strong coupling between polaritons and magnetic ions embedded in the semiconductor. We investigate the effect of the nonequilibrium nature of excit...
0
1
0
0
0
0
Inference in Sparse Graphs with Pairwise Measurements and Side Information
We consider the statistical problem of recovering a hidden "ground truth" binary labeling for the vertices of a graph up to low Hamming error from noisy edge and vertex measurements. We present new algorithms and a sharp finite-sample analysis for this problem on trees and sparse graphs with poor expansion properties...
1
0
0
0
0
0
Oracle Importance Sampling for Stochastic Simulation Models
We consider the problem of estimating an expected outcome from a stochastic simulation model using importance sampling. We propose a two-stage procedure that involves a regression stage and a sampling stage to construct our estimator. We introduce a parametric and a nonparametric regression estimator in the first sta...
0
0
0
1
0
0
The Generalized Cross Validation Filter
Generalized cross validation (GCV) is one of the most important approaches used to estimate parameters in the context of inverse problems and regularization techniques. A notable example is the determination of the smoothness parameter in splines. When the data are generated by a state space model, like in the spline...
1
0
0
1
0
0
Coherence of Biochemical Oscillations is Bounded by Driving Force and Network Topology
Biochemical oscillations are prevalent in living organisms. Systems with a small number of constituents cannot sustain coherent oscillations for an indefinite time because of fluctuations in the period of oscillation. We show that the number of coherent oscillations that quantifies the precision of the oscillator is ...
0
1
0
0
0
0
How Do Classifiers Induce Agents To Invest Effort Strategically?
Algorithms are often used to produce decision-making rules that classify or evaluate individuals. When these individuals have incentives to be classified a certain way, they may behave strategically to influence their outcomes. We develop a model for how strategic agents can invest effort in order to change the outco...
0
0
0
1
0
0
Guiding Reinforcement Learning Exploration Using Natural Language
In this work we present a technique to use natural language to help reinforcement learning generalize to unseen environments. This technique uses neural machine translation, specifically the use of encoder-decoder networks, to learn associations between natural language behavior descriptions and state-action informat...
1
0
0
1
0
0
Of the People: Voting Is More Effective with Representative Candidates
In light of the classic impossibility results of Arrow and Gibbard and Satterthwaite regarding voting with ordinal rules, there has been recent interest in characterizing how well common voting rules approximate the social optimum. In order to quantify the quality of approximation, it is natural to consider the candi...
1
0
0
0
0
0
Cell Coverage Extension with Orthogonal Random Precoding for Massive MIMO Systems
In this paper, we investigate a coverage extension scheme based on orthogonal random precoding (ORP) for the downlink of massive multiple-input multiple-output (MIMO) systems. In this scheme, a precoding matrix consisting of orthogonal vectors is employed at the transmitter to enhance the maximum signal-to-interferen...
1
0
1
0
0
0
Hidden Community Detection in Social Networks
We introduce a new paradigm that is important for community detection in the realm of network analysis. Networks contain a set of strong, dominant communities, which interfere with the detection of weak, natural community structure. When most of the members of the weak communities also belong to stronger communities,...
1
1
0
1
0
0
Two-photon exchange correction to the hyperfine splitting in muonic hydrogen
We reevaluate the Zemach, recoil and polarizability corrections to the hyperfine splitting in muonic hydrogen expressing them through the low-energy proton structure constants and obtain the precise values of the Zemach radius and two-photon exchange (TPE) contribution. The uncertainty of TPE correction to S energy l...
0
1
0
0
0
0
Ising Models with Latent Conditional Gaussian Variables
Ising models describe the joint probability distribution of a vector of binary feature variables. Typically, not all the variables interact with each other and one is interested in learning the presumably sparse network structure of the interacting variables. However, in the presence of latent variables, the conventi...
1
0
0
1
0
0
Quasiparticles and charge transfer at the two surfaces of the honeycomb iridate Na$_2$IrO$_3$
Direct experimental investigations of the low-energy electronic structure of the Na$_2$IrO$_3$ iridate insulator are sparse and draw two conflicting pictures. One relies on flat bands and a clear gap, the other involves dispersive states approaching the Fermi level, pointing to surface metallicity. Here, by a combina...
0
1
0
0
0
0
Breaking Bivariate Records
We establish a fundamental property of bivariate Pareto records for independent observations uniformly distributed in the unit square. We prove that the asymptotic conditional distribution of the number of records broken by an observation given that the observation sets a record is Geometric with parameter 1/2.
0
0
1
1
0
0
A Bag-of-Paths Node Criticality Measure
This work compares several node (and network) criticality measures quantifying to which extend each node is critical with respect to the communication flow between nodes of the network, and introduces a new measure based on the Bag-of-Paths (BoP) framework. Network disconnection simulation experiments show that the n...
1
1
0
0
0
0
Generation and analysis of lamplighter programs
We consider a programming language based on the lamplighter group that uses only composition and iteration as control structures. We derive generating functions and counting formulas for this language and special subsets of it, establishing lower and upper bounds on the growth rate of semantically distinct programs. ...
1
0
1
0
0
0
A Projection-Based Reformulation and Decomposition Algorithm for Global Optimization of a Class of Mixed Integer Bilevel Linear Programs
We propose an extended variant of the reformulation and decomposition algorithm for solving a special class of mixed-integer bilevel linear programs (MIBLPs) where continuous and integer variables are involved in both upper- and lower-level problems. In particular, we consider MIBLPs with upper-level constraints that...
0
0
1
0
0
0
Preduals for spaces of operators involving Hilbert spaces and trace-class operators
Continuing the study of preduals of spaces $\mathcal{L}(H,Y)$ of bounded, linear maps, we consider the situation that $H$ is a Hilbert space. We establish a natural correspondence between isometric preduals of $\mathcal{L}(H,Y)$ and isometric preduals of $Y$. The main ingredient is a Tomiyama-type result which shows ...
0
0
1
0
0
0
Computing maximum cliques in $B_2$-EPG graphs
EPG graphs, introduced by Golumbic et al. in 2009, are edge-intersection graphs of paths on an orthogonal grid. The class $B_k$-EPG is the subclass of EPG graphs where the path on the grid associated to each vertex has at most $k$ bends. Epstein et al. showed in 2013 that computing a maximum clique in $B_1$-EPG graph...
1
0
0
0
0
0
Interactions between Health Searchers and Search Engines
The Web is an important resource for understanding and diagnosing medical conditions. Based on exposure to online content, people may develop undue health concerns, believing that common and benign symptoms are explained by serious illnesses. In this paper, we investigate potential strategies to mine queries and sear...
1
0
0
0
0
0
Effect algebras as presheaves on finite Boolean algebras
For an effect algebra $A$, we examine the category of all morphisms from finite Boolean algebras into $A$. This category can be described as a category of elements of a presheaf $R(A)$ on the category of finite Boolean algebras. We prove that some properties (being an orthoalgebra, the Riesz decomposition property, b...
0
0
1
0
0
0
Training Deep Convolutional Neural Networks with Resistive Cross-Point Devices
In a previous work we have detailed the requirements to obtain a maximal performance benefit by implementing fully connected deep neural networks (DNN) in form of arrays of resistive devices for deep learning. This concept of Resistive Processing Unit (RPU) devices we extend here towards convolutional neural networks...
1
0
0
1
0
0
Absolute versus convective helical magnetorotational instabilities in Taylor-Couette flows
We study magnetic Taylor-Couette flow in a system having nondimensional radii $r_i=1$ and $r_o=2$, and periodic in the axial direction with wavelengths $h\ge100$. The rotation ratio of the inner and outer cylinders is adjusted to be slightly in the Rayleigh-stable regime, where magnetic fields are required to destabi...
0
1
0
0
0
0
Symmetries and multipeakon solutions for the modified two-component Camassa-Holm system
Compared with the two-component Camassa-Holm system, the modified two-component Camassa-Holm system introduces a regularized density which makes possible the existence of solutions of lower regularity, and in particular of multipeakon solutions. In this paper, we derive a new pointwise invariant for the modified two-...
0
0
1
0
0
0
Selection of quasi-stationary states in the Navier-Stokes equation on the torus
The two dimensional incompressible Navier-Stokes equation on $D_\delta := [0, 2\pi\delta] \times [0, 2\pi]$ with $\delta \approx 1$, periodic boundary conditions, and viscosity $0 < \nu \ll 1$ is considered. Bars and dipoles, two explicitly given quasi-stationary states of the system, evolve on the time scale $\mathc...
0
0
1
0
0
0
Geometric Enclosing Networks
Training model to generate data has increasingly attracted research attention and become important in modern world applications. We propose in this paper a new geometry-based optimization approach to address this problem. Orthogonal to current state-of-the-art density-based approaches, most notably VAE and GAN, we pr...
1
0
0
1
0
0
A pliable lasso for the Cox model
We introduce a pliable lasso method for estimation of interaction effects in the Cox proportional hazards model framework. The pliable lasso is a linear model that includes interactions between covariates X and a set of modifying variables Z and assumes sparsity of the main effects and interaction effects. The hierar...
0
0
0
1
0
0
Localized magnetic moments with tunable spin exchange in a gas of ultracold fermions
We report on the experimental realization of a state-dependent lattice for a two-orbital fermionic quantum gas with strong interorbital spin exchange. In our state-dependent lattice, the ground and metastable excited electronic states of $^{173}$Yb take the roles of itinerant and localized magnetic moments, respectiv...
0
1
0
0
0
0
Khintchine's Theorem with random fractions
We prove versions of Khintchine's Theorem (1924) for approximations by rational numbers whose numerators lie in randomly chosen sets of integers, and we explore the extent to which the monotonicity assumption can be removed. Roughly speaking, we show that if the number of available fractions for each denominator grow...
0
0
1
0
0
0
A Method of Generating Random Weights and Biases in Feedforward Neural Networks with Random Hidden Nodes
Neural networks with random hidden nodes have gained increasing interest from researchers and practical applications. This is due to their unique features such as very fast training and universal approximation property. In these networks the weights and biases of hidden nodes determining the nonlinear feature mapping...
1
0
0
1
0
0
The Relative Performance of Ensemble Methods with Deep Convolutional Neural Networks for Image Classification
Artificial neural networks have been successfully applied to a variety of machine learning tasks, including image recognition, semantic segmentation, and machine translation. However, few studies fully investigated ensembles of artificial neural networks. In this work, we investigated multiple widely used ensemble me...
1
0
0
1
0
0
Representation of big data by dimension reduction
Suppose the data consist of a set $S$ of points $x_j, 1 \leq j \leq J$, distributed in a bounded domain $D \subset R^N$, where $N$ and $J$ are large numbers. In this paper an algorithm is proposed for checking whether there exists a manifold $\mathbb{M}$ of low dimension near which many of the points of $S$ lie and f...
1
0
0
1
0
0
Out-degree reducing partitions of digraphs
Let $k$ be a fixed integer. We determine the complexity of finding a $p$-partition $(V_1, \dots, V_p)$ of the vertex set of a given digraph such that the maximum out-degree of each of the digraphs induced by $V_i$, ($1\leq i\leq p$) is at least $k$ smaller than the maximum out-degree of $D$. We show that this problem...
1
0
0
0
0
0
Introduction to Plasma Physics
These notes are intended to provide a brief primer in plasma physics, introducing common definitions, basic properties, and typical processes found in plasmas. These concepts are inherent in contemporary plasma-based accelerator schemes, and thus provide a foundation for the more advanced expositions that follow in t...
0
1
0
0
0
0
Presymplectic convexity and (ir)rational polytopes
In this paper, we extend the Atiyah--Guillemin--Sternberg convexity theorem and Delzant's classification of symplectic toric manifolds to presymplectic manifolds. We also define and study the Morita equivalence of presymplectic toric manifolds and of their corresponding framed momentum polytopes, which may be rationa...
0
0
1
0
0
0
Unsupervised Learning of Mixture Regression Models for Longitudinal Data
This paper is concerned with learning of mixture regression models for individuals that are measured repeatedly. The adjective "unsupervised" implies that the number of mixing components is unknown and has to be determined, ideally by data driven tools. For this purpose, a novel penalized method is proposed to simult...
0
0
0
1
0
0
Anomalous electron states
By the certain macroscopic perturbations in condensed matter anomalous electron wells can be formed due to a local reduction of electromagnetic zero point energy. These wells are narrow, of the width $\sim 10^{-11}cm$, and with the depth $\sim 1MeV$. Such anomalous states, from the formal standpoint of quantum mechan...
0
1
0
0
0
0
Theoretical calculation of the fine-structure constant and the permittivity of the vacuum
Light traveling through the vacuum interacts with virtual particles similarly to the way that light traveling through a dielectric interacts with ordinary matter. And just as the permittivity of a dielectric can be calculated, the permittivity $\epsilon_0$ of the vacuum can be calculated, yielding an equation for the...
0
1
0
0
0
0
LEADER: fast estimates of asteroid shape elongation and spin latitude distributions from scarce photometry
Many asteroid databases with lightcurve brightness measurements (e.g. WISE, Pan-STARRS1) contain enormous amounts of data for asteroid shape and spin modelling. While lightcurve inversion is not plausible for individual targets with scarce data, it is possible for large populations with thousands of asteroids, where ...
0
1
0
0
0
0
Calibrated Projection in MATLAB: Users' Manual
We present the calibrated-projection MATLAB package implementing the method to construct confidence intervals proposed by Kaido, Molinari and Stoye (2017). This manual provides details on how to use the package for inference on projections of partially identified parameters. It also explains how to use the MATLAB fun...
0
0
0
1
0
0
Atomic Clock Measurements of Quantum Scattering Phase Shifts Spanning Feshbach Resonances at Ultralow Fields
We use an atomic fountain clock to measure quantum scattering phase shifts precisely through a series of narrow, low-field Feshbach resonances at average collision energies below $1\,\mu$K. Our low spread in collision energy yields phase variations of order $\pm \pi/2$ for target atoms in several $F,m_F$ states. We c...
0
1
0
0
0
0
Temporal processing and context dependency in C. elegans mechanosensation
A quantitative understanding of how sensory signals are transformed into motor outputs places useful constraints on brain function and helps reveal the brain's underlying computations. We investigate how the nematode C. elegans responds to time-varying mechanosensory signals using a high-throughput optogenetic assay ...
0
0
0
0
1
0
On the putative essential discreteness of q-generalized entropies
It has been argued in [EPL {\bf 90} (2010) 50004], entitled {\it Essential discreteness in generalized thermostatistics with non-logarithmic entropy}, that "continuous Hamiltonian systems with long-range interactions and the so-called q-Gaussian momentum distributions are seen to be outside the scope of non-extensive...
0
1
0
0
0
0
Spin Distribution of Primordial Black Holes
We estimate the spin distribution of primordial black holes based on the recent study of the critical phenomena in the gravitational collapse of a rotating radiation fluid. We find that primordial black holes are mostly slowly rotating.
0
1
0
0
0
0
Automated flow for compressing convolution neural networks for efficient edge-computation with FPGA
Deep convolutional neural networks (CNN) based solutions are the current state- of-the-art for computer vision tasks. Due to the large size of these models, they are typically run on clusters of CPUs or GPUs. However, power requirements and cost budgets can be a major hindrance in adoption of CNN for IoT applications...
1
0
0
0
0
0
Pulse rate estimation using imaging photoplethysmography: generic framework and comparison of methods on a publicly available dataset
Objective: to establish an algorithmic framework and a benchmark dataset for comparing methods of pulse rate estimation using imaging photoplethysmography (iPPG). Approach: first we reveal essential steps of pulse rate estimation from facial video and review methods applied at each of the steps. Then we investigate p...
0
1
0
0
0
0
Deep Laplacian Pyramid Networks for Fast and Accurate Super-Resolution
Convolutional neural networks have recently demonstrated high-quality reconstruction for single-image super-resolution. In this paper, we propose the Laplacian Pyramid Super-Resolution Network (LapSRN) to progressively reconstruct the sub-band residuals of high-resolution images. At each pyramid level, our model take...
1
0
0
0
0
0
Foundation for a series of efficient simulation algorithms
Compute the coarsest simulation preorder included in an initial preorder is used to reduce the resources needed to analyze a given transition system. This technique is applied on many models like Kripke structures, labeled graphs, labeled transition systems or even word and tree automata. Let (Q, $\rightarrow$) be a ...
1
0
0
0
0
0
A Review of Macroscopic Motion in Thermodynamic Equilibrium
A principle on the macroscopic motion of systems in thermodynamic equilibrium, rarely discussed in texts, is reviewed: Very small but still macroscopic parts of a fully isolated system in thermal equilibrium move as if points of a rigid body, macroscopic energy being dissipated to increase internal energy, and increa...
0
1
0
0
0
0
Emergent electronic structure of CaFe2As2
CaFe2As2 exhibits collapsed tetragonal (cT) structure and varied exotic behavior under pressure at low temperatures that led to debate on linking the structural changes to its exceptional electronic properties like superconductivity, magnetism, etc. Here, we investigate the electronic structure of CaFe2As2 forming in...
0
1
0
0
0
0
Lord Kelvin's method of images approach to the Rotenberg model and its asymptotics
We study a mathematical model of cell populations dynamics proposed by M. Rotenberg and investigated by M. Boulanouar. Here, a cell is characterized by her maturity and speed of maturation. The growth of cell populations is described by a partial differential equation with a boundary condition. In the first part of t...
0
0
1
0
0
0
Study of the Magnetizing Relationship of the Kickers for CSNS
The extraction system of CSNS mainly consists of two kinds of magnets: eight kickers and one lambertson magnet. In this paper, firstly, the magnetic test results of the eight kickers were introduced and then the filed uniformity and magnetizing relationship of the kickers were given. Secondly, during the beam commiss...
0
1
0
0
0
0
Smart "Predict, then Optimize"
Many real-world analytics problems involve two significant challenges: prediction and optimization. Due to the typically complex nature of each challenge, the standard paradigm is to predict, then optimize. By and large, machine learning tools are intended to minimize prediction error and do not account for how the p...
1
0
0
1
0
0
U-SLADS: Unsupervised Learning Approach for Dynamic Dendrite Sampling
Novel data acquisition schemes have been an emerging need for scanning microscopy based imaging techniques to reduce the time in data acquisition and to minimize probing radiation in sample exposure. Varies sparse sampling schemes have been studied and are ideally suited for such applications where the images can be ...
0
0
0
1
0
0
On a registration-based approach to sensor network localization
We consider a registration-based approach for localizing sensor networks from range measurements. This is based on the assumption that one can find overlapping cliques spanning the network. That is, for each sensor, one can identify geometric neighbors for which all inter-sensor ranges are known. Such cliques can be ...
1
0
1
0
0
0
Density estimation on small datasets
How might a smooth probability distribution be estimated, with accurately quantified uncertainty, from a limited amount of sampled data? Here we describe a field-theoretic approach that addresses this problem remarkably well in one dimension, providing an exact nonparametric Bayesian posterior without relying on tuna...
1
0
0
0
1
0
Generalized Euler classes, differential forms and commutative DGAs
In the context of commutative differential graded algebras over $\mathbb Q$, we show that an iteration of "odd spherical fibration" creates a "total space" commutative differential graded algebra with only odd degree cohomology. Then we show for such a commutative differential graded algebra that, for any of its "fib...
0
0
1
0
0
0
Episodic memory for continual model learning
Both the human brain and artificial learning agents operating in real-world or comparably complex environments are faced with the challenge of online model selection. In principle this challenge can be overcome: hierarchical Bayesian inference provides a principled method for model selection and it converges on the s...
1
0
0
1
0
0
Security Trust Zone in 5G Networks
Fifth Generation (5G) telecommunication system is going to deliver a flexible radio access network (RAN). Security functions such as authorization, authentication and accounting (AAA) are expected to be distributed from central clouds to edge clouds. We propose a novel architectural security solution that applies to ...
1
0
0
0
0
0
Upper-Bounding the Regularization Constant for Convex Sparse Signal Reconstruction
Consider reconstructing a signal $x$ by minimizing a weighted sum of a convex differentiable negative log-likelihood (NLL) (data-fidelity) term and a convex regularization term that imposes a convex-set constraint on $x$ and enforces its sparsity using $\ell_1$-norm analysis regularization. We compute upper bounds on...
0
0
1
1
0
0
On the Privacy of the Opal Data Release: A Response
This document is a response to a report from the University of Melbourne on the privacy of the Opal dataset release. The Opal dataset was released by Data61 (CSIRO) in conjunction with the Transport for New South Wales (TfNSW). The data consists of two separate weeks of "tap-on/tap-off" data of individuals who used a...
1
0
0
0
0
0
Long time behavior of Gross-Pitaevskii equation at positive temperature
The stochastic Gross-Pitaevskii equation is used as a model to describe Bose-Einstein condensation at positive temperature. The equation is a complex Ginzburg Landau equation with a trapping potential and an additive space-time white noise. Two important questions for this system are the global existence of solutions...
0
0
1
0
0
0
Isomorphism and Morita equivalence classes for crossed products of irrational rotation algebras by cyclic subgroups of $SL_2(\mathbb{Z})$
Let $\theta, \theta'$ be irrational numbers and $A, B$ be matrices in $SL_2(\mathbb{Z})$ of infinite order. We compute the $K$-theory of the crossed product $\mathcal{A}_{\theta}\rtimes_A \mathbb{Z}$ and show that $\mathcal{A}_{\theta} \rtimes_A\mathbb{Z}$ and $\mathcal{A}_{\theta'} \rtimes_B \mathbb{Z}$ are $*$-isom...
0
0
1
0
0
0
Model Predictive Control for Distributed Microgrid Battery Energy Storage Systems
This paper proposes a new convex model predictive control strategy for dynamic optimal power flow between battery energy storage systems distributed in an AC microgrid. The proposed control strategy uses a new problem formulation, based on a linear d-q reference frame voltage-current model and linearised power flow a...
1
0
0
0
0
0
On noncommutative geometry of the Standard Model: fermion multiplet as internal forms
We unveil the geometric nature of the multiplet of fundamental fermions in the Standard Model of fundamental particles as a noncommutative analogue of de Rham forms on the internal finite quantum space.
0
0
1
0
0
0
A Review of Dynamic Network Models with Latent Variables
We present a selective review of statistical modeling of dynamic networks. We focus on models with latent variables, specifically, the latent space models and the latent class models (or stochastic blockmodels), which investigate both the observed features and the unobserved structure of networks. We begin with an ov...
0
0
0
1
0
0
LevelHeaded: Making Worst-Case Optimal Joins Work in the Common Case
Pipelines combining SQL-style business intelligence (BI) queries and linear algebra (LA) are becoming increasingly common in industry. As a result, there is a growing need to unify these workloads in a single framework. Unfortunately, existing solutions either sacrifice the inherent benefits of exclusively using a re...
1
0
0
0
0
0
Few-shot learning of neural networks from scratch by pseudo example optimization
In this paper, we propose a simple but effective method for training neural networks with a limited amount of training data. Our approach inherits the idea of knowledge distillation that transfers knowledge from a deep or wide reference model to a shallow or narrow target model. The proposed method employs this idea ...
0
0
0
1
0
0
Identities and congruences involving the Fubini polynomials
In this paper, we investigate the umbral representation of the Fubini polynomials $F_{x}^{n}:=F_{n}(x)$ to derive some properties involving these polynomials. For any prime number $p$ and any polynomial $f$ with integer coefficients, we show $(f(F_{x}))^{p}\equiv f(F_{x})$ and we give other curious congruences.
0
0
1
0
0
0
Introduction to Delay Models and Their Wave Solutions
In this paper, a brief review of delay population models and their applications in ecology is provided. The inclusion of diffusion and nonlocality terms in delay models has given more capabilities to these models enabling them to capture several ecological phenomena such as the Allee effect, waves of invasive species...
0
0
1
0
0
0
On Dummett's Pragmatist Justification Procedure
I show that propositional intuitionistic logic is complete with respect to an adaptation of Dummett's pragmatist justification procedure. In particular, given a pragmatist justification of an argument, I show how to obtain a natural deduction derivation of the conclusion of the argument from, at most, the same assump...
0
0
1
0
0
0
Evidence for a radiatively driven disc-wind in PDS 456?
We present a newly discovered correlation between the wind outflow velocity and the X-ray luminosity in the luminous ($L_{\rm bol}\sim10^{47}\,\rm erg\,s^{-1}$) nearby ($z=0.184$) quasar PDS\,456. All the contemporary XMM-Newton, NuSTAR and Suzaku observations from 2001--2014 were revisited and we find that the centr...
0
1
0
0
0
0
From a normal insulator to a topological insulator in plumbene
Plumbene, similar to silicene, has a buckled honeycomb structure with a large band gap ($\sim 400$ meV). All previous studies have shown that it is a normal insulator. Here, we perform first-principles calculations and employ a sixteen-band tight-binding model with nearest-neighbor and next-nearest-neighbor hopping t...
0
1
0
0
0
0
High-sensitivity Kinetic Inductance Detectors for CALDER
Providing a background discrimination tool is crucial for enhancing the sensitivity of next-generation experiments searching for neutrinoless double- beta decay. The development of high-sensitivity (< 20 eV RMS) cryogenic light detectors allows simultaneous read-out of the light and heat signals and enables backgroun...
0
1
0
0
0
0
Bounding the composition length of primitive permutation groups and completely reducible linear groups
We obtain upper bounds on the composition length of a finite permutation group in terms of the degree and the number of orbits, and analogous bounds for primitive, quasiprimitive and semiprimitive groups. Similarly, we obtain upper bounds on the composition length of a finite completely reducible linear group in term...
0
0
1
0
0
0
A Bernstein Inequality For Spatial Lattice Processes
In this article we present a Bernstein inequality for sums of random variables which are defined on a spatial lattice structure. The inequality can be used to derive concentration inequalities. It can be useful to obtain consistency properties for nonparametric estimators of conditional expectation functions.
0
0
1
1
0
0
An Exploration of Approaches to Integrating Neural Reranking Models in Multi-Stage Ranking Architectures
We explore different approaches to integrating a simple convolutional neural network (CNN) with the Lucene search engine in a multi-stage ranking architecture. Our models are trained using the PyTorch deep learning toolkit, which is implemented in C/C++ with a Python frontend. One obvious integration strategy is to e...
1
0
0
0
0
0
Dispersive Regimes of the Dicke Model
We study two dispersive regimes in the dynamics of $N$ two-level atoms interacting with a bosonic mode for long interaction times. Firstly, we analyze the dispersive multiqubit quantum Rabi model for the regime in which the qubit frequencies are equal and smaller than the mode frequency, and for values of the couplin...
0
1
0
0
0
0
ZebraLancer: Crowdsource Knowledge atop Open Blockchain, Privately and Anonymously
We design and implement the first private and anonymous decentralized crowdsourcing system ZebraLancer. It realizes the fair exchange (i.e. security against malicious workers and dishonest requesters) without using any third-party arbiter. More importantly, it overcomes two fundamental challenges of decentralization,...
1
0
0
0
0
0
Fast, Better Training Trick -- Random Gradient
In this paper, we will show an unprecedented method to accelerate training and improve performance, which called random gradient (RG). This method can be easier to the training of any model without extra calculation cost, we use Image classification, Semantic segmentation, and GANs to confirm this method can improve ...
0
0
0
1
0
0
Expressions of Sentiments During Code Reviews: Male vs. Female
Background: As most of the software development organizations are male-dominated, female developers encountering various negative workplace experiences reported feeling like they "do not belong". Exposures to discriminatory expletives or negative critiques from their male colleagues may further exacerbate those feeli...
1
0
0
0
0
0
Monotonicity patterns and functional inequalities for classical and generalized Wright functions
In this paper our aim is to present the completely monotonicity and convexity properties for the Wright function. As consequences of these results, we present some functional inequalities. Moreover, we derive the monotonicity and log-convexity results for the generalized Wright functions. As applications, we present ...
0
0
1
0
0
0
Multiple VLAD encoding of CNNs for image classification
Despite the effectiveness of convolutional neural networks (CNNs) especially in image classification tasks, the effect of convolution features on learned representations is still limited. It mostly focuses on the salient object of the images, but ignores the variation information on clutter and local. In this paper, ...
1
0
0
0
0
0
Index of Dirac operators and classification of topological insulators
Real and complex Clifford bundles and Dirac operators defined on them are considered. By using the index theorems of Dirac operators, table of topological invariants is constructed from the Clifford chessboard. Through the relations between K-theory groups, Grothendieck groups and symmetric spaces, the periodic table...
0
1
0
0
0
0
Centroid vetting of transiting planet candidates from the Next Generation Transit Survey
The Next Generation Transit Survey (NGTS), operating in Paranal since 2016, is a wide-field survey to detect Neptunes and super-Earths transiting bright stars, which are suitable for precise radial velocity follow-up and characterisation. Thereby, its sub-mmag photometric precision and ability to identify false posit...
0
1
0
0
0
0
Galaxy And Mass Assembly: the evolution of the cosmic spectral energy distribution from z = 1 to z = 0
We present the evolution of the Cosmic Spectral Energy Distribution (CSED) from $z = 1 - 0$. Our CSEDs originate from stacking individual spectral energy distribution fits based on panchromatic photometry from the Galaxy and Mass Assembly (GAMA) and COSMOS datasets in ten redshift intervals with completeness correcti...
0
1
0
0
0
0
Large sums of Hecke eigenvalues of holomorphic cusp forms
Let $f$ be a Hecke cusp form of weight $k$ for the full modular group, and let $\{\lambda_f(n)\}_{n\geq 1}$ be the sequence of its normalized Fourier coefficients. Motivated by the problem of the first sign change of $\lambda_f(n)$, we investigate the range of $x$ (in terms of $k$) for which there are cancellations i...
0
0
1
0
0
0
EAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial Examples
Recent studies have highlighted the vulnerability of deep neural networks (DNNs) to adversarial examples - a visually indistinguishable adversarial image can easily be crafted to cause a well-trained model to misclassify. Existing methods for crafting adversarial examples are based on $L_2$ and $L_\infty$ distortion ...
1
0
0
1
0
0
Playtime Measurement with Survival Analysis
Maximizing product use is a central goal of many businesses, which makes retention and monetization two central analytics metrics in games. Player retention may refer to various duration variables quantifying product use: total playtime or session playtime are popular research targets, and active playtime is well-sui...
1
0
0
1
0
0
Asymptotic formula of the number of Newton polygons
In this paper, we enumerate Newton polygons asymptotically. The number of Newton polygons is computable by a simple recurrence equation, but unexpectedly the asymptotic formula of its logarithm contains growing oscillatory terms. As the terms come from non-trivial zeros of the Riemann zeta function, an estimation of ...
0
0
1
0
0
0
Invariant-based inverse engineering of crane control parameters
By applying invariant-based inverse engineering in the small-oscillations regime, we design the time dependence of the control parameters of an overhead crane (trolley displacement and rope length), to transport a load between two positions at different heights with minimal final energy excitation for a microcanonica...
0
1
0
0
0
0
Leaf Space Isometries of Singular Riemannian Foliations and Their Spectral Properties
In this paper, the authors consider leaf spaces of singular Riemannian foliations $\mathcal{F}$ on compact manifolds $M$ and the associated $\mathcal{F}$-basic spectrum on $M$, $spec_B(M, \mathcal{F}),$ counted with multiplicities. Recently, a notion of smooth isometry $\varphi: M_1/\mathcal{F}_1\rightarrow M_2/\math...
0
0
1
0
0
0
Backward Monte-Carlo applied to muon transport
We discuss a backward Monte-Carlo technique for muon transport problem, with emphasis on its application in muography. Backward Monte-Carlo allows exclusive sampling of a final state by reversing the simulation flow. In practice it can be made analogous to an adjoint Monte-Carlo, though it is more versatile for muon ...
0
1
0
0
0
0
Functional importance of noise in neuronal information processing
Noise is an inherent part of neuronal dynamics, and thus of the brain. It can be observed in neuronal activity at different spatiotemporal scales, including in neuronal membrane potentials, local field potentials, electroencephalography, and magnetoencephalography. A central research topic in contemporary neuroscienc...
0
0
0
0
1
0
Stochastic Variance Reduction Methods for Policy Evaluation
Policy evaluation is a crucial step in many reinforcement-learning procedures, which estimates a value function that predicts states' long-term value under a given policy. In this paper, we focus on policy evaluation with linear function approximation over a fixed dataset. We first transform the empirical policy eval...
1
0
1
1
0
0