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
Tangle-tree duality in abstract separation systems
We prove a general width duality theorem for combinatorial structures with well-defined notions of cohesion and separation. These might be graphs and matroids, but can be much more general or quite different. The theorem asserts a duality between the existence of high cohesiveness somewhere local and a global overall...
0
0
1
0
0
0
Attention-Based Guided Structured Sparsity of Deep Neural Networks
Network pruning is aimed at imposing sparsity in a neural network architecture by increasing the portion of zero-valued weights for reducing its size regarding energy-efficiency consideration and increasing evaluation speed. In most of the conducted research efforts, the sparsity is enforced for network pruning witho...
0
0
0
1
0
0
A Graph Model with Indirect Co-location Links
Graph models are widely used to analyse diffusion processes embedded in social contacts and to develop applications. A range of graph models are available to replicate the underlying social structures and dynamics realistically. However, most of the current graph models can only consider concurrent interactions among...
1
0
0
0
0
0
Essentially No Barriers in Neural Network Energy Landscape
Training neural networks involves finding minima of a high-dimensional non-convex loss function. Knowledge of the structure of this energy landscape is sparse. Relaxing from linear interpolations, we construct continuous paths between minima of recent neural network architectures on CIFAR10 and CIFAR100. Surprisingly...
0
0
0
1
0
0
Homogenization of nonlinear elliptic systems in nonreflexive Musielak-Orlicz spaces
We study the homogenization process for families of strongly nonlinear elliptic systems with the homogeneous Dirichlet boundary conditions. The growth and the coercivity of the elliptic operator is assumed to be indicated by a general inhomogeneous anisotropic $N-$function, which may be possibly also dependent on the...
0
0
1
0
0
0
A Generalization of Permanent Inequalities and Applications in Counting and Optimization
A polynomial $p\in\mathbb{R}[z_1,\dots,z_n]$ is real stable if it has no roots in the upper-half complex plane. Gurvits's permanent inequality gives a lower bound on the coefficient of the $z_1z_2\dots z_n$ monomial of a real stable polynomial $p$ with nonnegative coefficients. This fundamental inequality has been us...
1
0
1
0
0
0
Proceedings Fifth International Workshop on Verification and Program Transformation
This volume contains the proceedings of the Fifth International Workshop on Verification and Program Transformation (VPT 2017). The workshop took place in Uppsala, Sweden, on April 29th, 2017, affiliated with the European Joint Conferences on Theory and Practice of Software (ETAPS). The aim of the VPT workshop series...
1
0
0
0
0
0
H-infinity Filtering for Cloud-Aided Semi-active Suspension with Delayed Information
This chapter presents an H-infinity filtering framework for cloud-aided semiactive suspension system with time-varying delays. In this system, road profile information is downloaded from a cloud database to facilitate onboard estimation of suspension states. Time-varying data transmission delays are considered and as...
1
0
0
0
0
0
Deep Spatio-Temporal Random Fields for Efficient Video Segmentation
In this work we introduce a time- and memory-efficient method for structured prediction that couples neuron decisions across both space at time. We show that we are able to perform exact and efficient inference on a densely connected spatio-temporal graph by capitalizing on recent advances on deep Gaussian Conditiona...
0
0
0
1
0
0
A Coherent vorticity preserving eddy viscosity correction for Large-Eddy Simulation
This paper introduces a new approach to Large-Eddy Simulation (LES) where subgrid-scale (SGS) dissipation is applied proportionally to the degree of local spectral broadening, hence mitigated or deactivated in regions dominated by large-scale and/or laminar vortical motion. The proposed Coherent vorticity preserving ...
1
1
0
0
0
0
A Universal Marginalizer for Amortized Inference in Generative Models
We consider the problem of inference in a causal generative model where the set of available observations differs between data instances. We show how combining samples drawn from the graphical model with an appropriate masking function makes it possible to train a single neural network to approximate all the correspo...
1
0
0
1
0
0
Approximating the Backbone in the Weighted Maximum Satisfiability Problem
The weighted Maximum Satisfiability problem (weighted MAX-SAT) is a NP-hard problem with numerous applications arising in artificial intelligence. As an efficient tool for heuristic design, the backbone has been applied to heuristics design for many NP-hard problems. In this paper, we investigated the computational c...
1
0
0
0
0
0
Fulde-Ferrell-Larkin-Ovchinnikov state in spin-orbit-coupled superconductors
We show that in the presence of magnetic field, two superconducting phases with the center-of-mass momentum of Cooper pair parallel to the magnetic field are induced in spin-orbit-coupled superconductor Li$_2$Pd$_3$B. Specifically, at small magnetic field, the center-of-mass momentum is induced due to the energy-spec...
0
1
0
0
0
0
New type integral inequalities for convex functions with applications II
We have recently established some integral inequalities for convex functions via the Hermite-Hadamard's inequalities. In continuation here, we also establish some interesting new integral inequalities for convex functions via the Hermite--Hadamard's inequalities and Jensen's integral inequality. Useful applications i...
0
0
1
0
0
0
Geometric Insights into Support Vector Machine Behavior using the KKT Conditions
The support vector machine (SVM) is a powerful and widely used classification algorithm. This paper uses the Karush-Kuhn-Tucker conditions to provide rigorous mathematical proof for new insights into the behavior of SVM. These insights provide perhaps unexpected relationships between SVM and two other linear classifi...
0
0
0
1
0
0
Smart Grids Data Analysis: A Systematic Mapping Study
Data analytics and data science play a significant role in nowadays society. In the context of Smart Grids (SG), the collection of vast amounts of data has seen the emergence of a plethora of data analysis approaches. In this paper, we conduct a Systematic Mapping Study (SMS) aimed at getting insights about different...
1
0
0
0
0
0
Physical problem solving: Joint planning with symbolic, geometric, and dynamic constraints
In this paper, we present a new task that investigates how people interact with and make judgments about towers of blocks. In Experiment~1, participants in the lab solved a series of problems in which they had to re-configure three blocks from an initial to a final configuration. We recorded whether they used one han...
1
0
0
1
0
0
Complex Networks: from Classical to Quantum
Recent progress in applying complex network theory to problems faced in quantum information and computation has resulted in a beneficial crossover between two fields. Complex network methods have successfully been used to characterize quantum walk and transport models, entangled communication networks, graph-theoreti...
1
1
0
0
0
0
On the K-theory of C*-algebras for substitution tilings (a pedestrian version)
Under suitable conditions, a substitution tiling gives rise to a Smale space, from which three equivalence relations can be constructed, namely the stable, unstable, and asymptotic equivalence relations. We denote with $S$, $U$, and $A$ their corresponding $C^*$-algebras in the sense of Renault. In this article we sh...
0
0
1
0
0
0
The Tutte embedding of the mated-CRT map converges to Liouville quantum gravity
We prove that the Tutte embeddings (a.k.a. harmonic/embeddings) of certain random planar maps converge to $\gamma$-Liouville quantum gravity ($\gamma$-LQG). Specifically, we treat mated-CRT maps, which are discretized matings of correlated continuum random trees, and $\gamma$ ranges from $0$ to $2$ as one varies the ...
0
0
1
0
0
0
On the Computation of the Shannon Capacity of a Discrete Channel with Noise
Muroga [M52] showed how to express the Shannon channel capacity of a discrete channel with noise [S49] as an explicit function of the transition probabilities. His method accommodates channels with any finite number of input symbols, any finite number of output symbols and any transition probability matrix. Silverman...
1
0
0
0
0
0
Gorenstein homological properties of tensor rings
Let $R$ be a two-sided noetherian ring and $M$ be a nilpotent $R$-bimodule, which is finitely generated on both sides. We study Gorenstein homological properties of the tensor ring $T_R(M)$. Under certain conditions, the ring $R$ is Gorenstein if and only if so is $T_R(M)$. We characterize Gorenstein projective $T_R(...
0
0
1
0
0
0
Compositional Human Pose Regression
Regression based methods are not performing as well as detection based methods for human pose estimation. A central problem is that the structural information in the pose is not well exploited in the previous regression methods. In this work, we propose a structure-aware regression approach. It adopts a reparameteriz...
1
0
0
0
0
0
Stochastic functional differential equations and sensitivity to their initial path
We consider systems with memory represented by stochastic functional differential equations. Substantially, these are stochastic differential equations with coefficients depending on the past history of the process itself. Such coefficients are hence defined on a functional space. Models with memory appear in many ap...
0
0
1
0
0
0
Remarks on Inner Functions and Optimal Approximants
We discuss the concept of inner function in reproducing kernel Hilbert spaces with an orthogonal basis of monomials and examine connections between inner functions and optimal polynomial approximants to $1/f$, where $f$ is a function in the space. We revisit some classical examples from this perspective, and show how...
0
0
1
0
0
0
A Stochastic Model for File Lifetime and Security in Data Center Networks
Data center networks are an important infrastructure in various applications of modern information technologies. Note that each data center always has a finite lifetime, thus once a data center fails, then it will lose all its storage files and useful information. For this, it is necessary to replicate and copy each ...
1
0
0
0
0
0
Asymptotic Confidence Regions for High-dimensional Structured Sparsity
In the setting of high-dimensional linear regression models, we propose two frameworks for constructing pointwise and group confidence sets for penalized estimators which incorporate prior knowledge about the organization of the non-zero coefficients. This is done by desparsifying the estimator as in van de Geer et a...
0
0
1
1
0
0
Building a Structured Query Engine
Finding patterns in data and being able to retrieve information from those patterns is an important task in Information retrieval. Complex search requirements which are not fulfilled by simple string matching and require exploring certain patterns in data demand a better query engine that can support searching via st...
1
0
0
0
0
0
A Theoretical Perspective of Solving Phaseless Compressed Sensing via Its Nonconvex Relaxation
As a natural extension of compressive sensing and the requirement of some practical problems, Phaseless Compressed Sensing (PCS) has been introduced and studied recently. Many theoretical results have been obtained for PCS with the aid of its convex relaxation. Motivated by successful applications of nonconvex relaxe...
0
0
1
0
0
0
A Comprehensive Study of Ly$α$ Emission in the High-redshift Galaxy Population
We present an exhaustive census of Lyman alpha (Ly$\alpha$) emission in the general galaxy population at $3<z<4.6$. We use the Michigan/Magellan Fiber System (M2FS) spectrograph to study a stellar mass (M$_*$) selected sample of 625 galaxies homogeneously distributed in the range $7.6<\log{\mbox{M$_*$/M$_{\odot}$}}<1...
0
1
0
0
0
0
Optimal Timing of Decisions: A General Theory Based on Continuation Values
Building on insights of Jovanovic (1982) and subsequent authors, we develop a comprehensive theory of optimal timing of decisions based around continuation value functions and operators that act on them. Optimality results are provided under general settings, with bounded or unbounded reward functions. This approach ...
0
0
1
0
0
0
OSIRIS-REx Contamination Control Strategy and Implementation
OSIRIS-REx will return pristine samples of carbonaceous asteroid Bennu. This article describes how pristine was defined based on expectations of Bennu and on a realistic understanding of what is achievable with a constrained schedule and budget, and how that definition flowed to requirements and implementation. To re...
0
1
0
0
0
0
Linear Stochastic Approximation: Constant Step-Size and Iterate Averaging
We consider $d$-dimensional linear stochastic approximation algorithms (LSAs) with a constant step-size and the so called Polyak-Ruppert (PR) averaging of iterates. LSAs are widely applied in machine learning and reinforcement learning (RL), where the aim is to compute an appropriate $\theta_{*} \in \mathbb{R}^d$ (th...
1
0
0
1
0
0
Curse of Heterogeneity: Computational Barriers in Sparse Mixture Models and Phase Retrieval
We study the fundamental tradeoffs between statistical accuracy and computational tractability in the analysis of high dimensional heterogeneous data. As examples, we study sparse Gaussian mixture model, mixture of sparse linear regressions, and sparse phase retrieval model. For these models, we exploit an oracle-bas...
0
0
0
1
0
0
Modality Attention for End-to-End Audio-visual Speech Recognition
Audio-visual speech recognition (AVSR) system is thought to be one of the most promising solutions for robust speech recognition, especially in noisy environment. In this paper, we propose a novel multimodal attention based method for audio-visual speech recognition which could automatically learn the fused represent...
1
0
0
0
0
0
Affine Rough Models
The goal of this survey article is to explain and elucidate the affine structure of recent models appearing in the rough volatility literature, and show how it leads to exponential-affine transform formulas.
0
0
0
0
0
1
When flux standards go wild: white dwarfs in the age of Kepler
White dwarf stars have been used as flux standards for decades, thanks to their staid simplicity. We have empirically tested their photometric stability by analyzing the light curves of 398 high-probability candidates and spectroscopically confirmed white dwarfs observed during the original Kepler mission and later w...
0
1
0
0
0
0
Multi-view Low-rank Sparse Subspace Clustering
Most existing approaches address multi-view subspace clustering problem by constructing the affinity matrix on each view separately and afterwards propose how to extend spectral clustering algorithm to handle multi-view data. This paper presents an approach to multi-view subspace clustering that learns a joint subspa...
1
0
0
1
0
0
Single-trial P300 Classification using PCA with LDA, QDA and Neural Networks
The P300 event-related potential (ERP), evoked in scalp-recorded electroencephalography (EEG) by external stimuli, has proven to be a reliable response for controlling a BCI. The P300 component of an event related potential is thus widely used in brain-computer interfaces to translate the subjects' intent by mere tho...
1
0
0
1
0
0
Stable representations of posets
The purpose of this paper is to study stable representations of partially ordered sets (posets) and compare it to the well known theory for quivers. In particular, we prove that every indecomposable representation of a poset of finite type is stable with respect to some weight and construct that weight explicitly in ...
0
0
1
0
0
0
Automatic segmentation of trees in dynamic outdoor environments
Segmentation in dynamic outdoor environments can be difficult when the illumination levels and other aspects of the scene cannot be controlled. Specifically in orchard and vineyard automation contexts, a background material is often used to shield a camera's field of view from other rows of crops. In this paper, we d...
1
0
0
0
0
0
A Practical Bandit Method with Advantages in Neural Network Tuning
Stochastic bandit algorithms can be used for challenging non-convex optimization problems. Hyperparameter tuning of neural networks is particularly challenging, necessitating new approaches. To this end, we present a method that adaptively partitions the combined space of hyperparameters, context, and training resour...
1
0
0
1
0
0
Dynamic Security Analysis of Power Systems by a Sampling-Based Algorithm
Dynamic security analysis is an important problem of power systems on ensuring safe operation and stable power supply even when certain faults occur. No matter such faults are caused by vulnerabilities of system components, physical attacks, or cyber-attacks that are more related to cyber-security, they eventually af...
1
0
0
0
0
0
Stochastic and Chance-Constrained Conic Distribution System Expansion Planning Using Bilinear Benders Decomposition
Second order conic programming (SOCP) has been used to model various applications in power systems, such as operation and expansion planning. In this paper, we present a two-stage stochastic mixed integer SOCP (MISOCP) model for the distribution system expansion planning problem that considers uncertainty and also ca...
0
0
1
0
0
0
Multi-Hop Extensions of Energy-Efficient Wireless Sensor Network Time Synchronization
We present the multi-hop extensions of the recently proposed energy-efficient time synchronization scheme for wireless sensor networks, which is based on the asynchronous source clock frequency recovery and reversed two-way message exchanges. We consider two hierarchical extensions based on packet relaying and time-t...
1
0
0
0
0
0
Value added or misattributed? A multi-institution study on the educational benefit of labs for reinforcing physics content
Instructional labs are widely seen as a unique, albeit expensive, way to teach scientific content. We measured the effectiveness of introductory lab courses at achieving this educational goal across nine different lab courses at three very different institutions. These institutions and courses encompassed a broad ran...
0
1
0
0
0
0
Smoothed Noise and Mexican Hat Coupling Produce Pattern in a Stochastic Neural Field
The formation of pattern in biological systems may be modeled by a set of reaction-diffusion equations. A diffusion-type coupling operator biologically significant in neuroscience is a difference of Gaussian functions (Mexican Hat operator) used as a spatial-convolution kernel. We are interested in the difference amo...
0
0
0
0
1
0
NeuroNER: an easy-to-use program for named-entity recognition based on neural networks
Named-entity recognition (NER) aims at identifying entities of interest in a text. Artificial neural networks (ANNs) have recently been shown to outperform existing NER systems. However, ANNs remain challenging to use for non-expert users. In this paper, we present NeuroNER, an easy-to-use named-entity recognition to...
1
0
0
1
0
0
Macro diversity in Cellular Networks with Random Blockages
Blocking objects (blockages) between a transmitter and receiver cause wireless communication links to transition from line-of-sight (LOS) to non-line-of-sight (NLOS) propagation, which can greatly reduce the received power, particularly at higher frequencies such as millimeter wave (mmWave). We consider a cellular ne...
1
0
1
0
0
0
Opinion dynamics model based on cognitive biases
We present an introduction to a novel model of an individual and group opinion dynamics, taking into account different ways in which different sources of information are filtered due to cognitive biases. The agent based model, using Bayesian updating of the individual belief distribution, is based on the recent psych...
1
1
0
0
0
0
ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness
Convolutional Neural Networks (CNNs) are commonly thought to recognise objects by learning increasingly complex representations of object shapes. Some recent studies suggest a more important role of image textures. We here put these conflicting hypotheses to a quantitative test by evaluating CNNs and human observers ...
0
0
0
0
1
0
Explicit evaluation of harmonic sums
In this paper, we obtain some formulae for harmonic sums, alternating harmonic sums and Stirling number sums by using the method of integral representations of series. As applications of these formulae, we give explicit formula of several quadratic and cubic Euler sums through zeta values and linear sums. Furthermore...
0
0
1
0
0
0
Complete Cyclic Proof Systems for Inductive Entailments
In this paper we develop cyclic proof systems for the problem of inclusion between the least sets of models of mutually recursive predicates, when the ground constraints in the inductive definitions belong to the quantifier-free fragments of (i) First Order Logic with the canonical Herbrand interpretation and (ii) Se...
1
0
0
0
0
0
HybridNet: Classification and Reconstruction Cooperation for Semi-Supervised Learning
In this paper, we introduce a new model for leveraging unlabeled data to improve generalization performances of image classifiers: a two-branch encoder-decoder architecture called HybridNet. The first branch receives supervision signal and is dedicated to the extraction of invariant class-related representations. The...
0
0
0
1
0
0
Learning Distributed Representations of Texts and Entities from Knowledge Base
We describe a neural network model that jointly learns distributed representations of texts and knowledge base (KB) entities. Given a text in the KB, we train our proposed model to predict entities that are relevant to the text. Our model is designed to be generic with the ability to address various NLP tasks with ea...
1
0
0
0
0
0
Moduli Spaces of Unordered $n\ge5$ Points on the Riemann Sphere and Their Singularities
For $n\ge5$, it is well known that the moduli space $\mathfrak{M_{0,\:n}}$ of unordered $n$ points on the Riemann sphere is a quotient space of the Zariski open set $K_n$ of $\mathbb C^{n-3}$ by an $S_n$ action. The stabilizers of this $S_n$ action at certain points of this Zariski open set $K_n$ correspond to the gr...
0
0
1
0
0
0
Multipath Error Correction in Radio Interferometric Positioning Systems
The radio interferometric positioning system (RIPS) is an accurate node localization method featuring a novel phase-based ranging process. Multipath is the limiting error source for RIPS in ground-deployed scenarios or indoor applications. There are four distinct channels involved in the ranging process for RIPS. Mul...
1
0
0
0
0
0
An evaluation homomorphism for quantum toroidal gl(n) algebras
We present an affine analog of the evaluation map for quantum groups. Namely we introduce a surjective homomorphism from the quantum toroidal gl(n) algebra to the quantum affine gl(n) algebra completed with respect to the homogeneous grading. We give a brief discussion of evaluation modules.
0
0
1
0
0
0
A Framework for Time-Consistent, Risk-Sensitive Model Predictive Control: Theory and Algorithms
In this paper we present a framework for risk-sensitive model predictive control (MPC) of linear systems affected by stochastic multiplicative uncertainty. Our key innovation is to consider a time-consistent, dynamic risk evaluation of the cumulative cost as the objective function to be minimized. This framework is a...
1
0
1
0
0
0
Monitoring Telluric Absorption with CAMAL
Ground-based astronomical observations may be limited by telluric water vapor absorption, which is highly variable in time and significantly complicates both spectroscopy and photometry in the near-infrared (NIR). To achieve the sensitivity required to detect Earth-sized exoplanets in the NIR, simultaneous monitoring...
0
1
0
0
0
0
Common Knowledge in a Logic of Gossips
Gossip protocols aim at arriving, by means of point-to-point or group communications, at a situation in which all the agents know each other secrets. Recently a number of authors studied distributed epistemic gossip protocols. These protocols use as guards formulas from a simple epistemic logic, which makes their ana...
1
0
0
0
0
0
Network-theoretic approach to sparsified discrete vortex dynamics
We examine discrete vortex dynamics in two-dimensional flow through a network-theoretic approach. The interaction of the vortices is represented with a graph, which allows the use of network-theoretic approaches to identify key vortex-to-vortex interactions. We employ sparsification techniques on these graph represen...
0
1
0
0
0
0
Bäcklund Transformation and Quasi-Integrable Deformation of Mixed Fermi-Pasta-Ulam and Frenkel-Kontorova Models
In this paper we study a non-linear partial differential equation (PDE), proposed by N. Kudryashov [arXiv:1611.06813v1[nlin.SI]], using continuum limit approximation of mixed Fermi-Pasta-Ulam and Frenkel-Kontorova Models. This generalized semi-discrete equation can be considered as a model for the description of non-...
0
1
1
0
0
0
Data-Mining Textual Responses to Uncover Misconception Patterns
An important, yet largely unstudied, problem in student data analysis is to detect misconceptions from students' responses to open-response questions. Misconception detection enables instructors to deliver more targeted feedback on the misconceptions exhibited by many students in their class, thus improving the quali...
1
0
0
1
0
0
Symmetries of handlebodies and their fixed points: Dihedral extended Schottky groups
A Schottky structure on a handlebody $M$ of genus $g$ is provided by a Schottky group of rank $g$. A symmetry (an orientation-reversing involution) of $M$ is known to have at most $(g+1)$ connected components of fixed points. Each of these components is either a point or a compact bordered surface (either orientable ...
0
0
1
0
0
0
Speaker Diarization using Deep Recurrent Convolutional Neural Networks for Speaker Embeddings
In this paper we propose a new method of speaker diarization that employs a deep learning architecture to learn speaker embeddings. In contrast to the traditional approaches that build their speaker embeddings using manually hand-crafted spectral features, we propose to train for this purpose a recurrent convolutiona...
1
0
0
0
0
0
A Robust Multi-Batch L-BFGS Method for Machine Learning
This paper describes an implementation of the L-BFGS method designed to deal with two adversarial situations. The first occurs in distributed computing environments where some of the computational nodes devoted to the evaluation of the function and gradient are unable to return results on time. A similar challenge oc...
1
0
1
1
0
0
Network of vertically c-oriented prism shaped InN nanowalls grown on c-GaN/sapphire template by chemical vapor deposition technique
Networks of vertically c-oriented prism shaped InN nanowalls, are grown on c-GaN/sapphire templates using a CVD technique, where pure indium and ammonia are used as metal and nitrogen precursors. A systematic study of the growth, structural and electronic properties of these samples shows a preferential growth of the...
0
1
0
0
0
0
Enhanced version of AdaBoostM1 with J48 Tree learning method
Machine Learning focuses on the construction and study of systems that can learn from data. This is connected with the classification problem, which usually is what Machine Learning algorithms are designed to solve. When a machine learning method is used by people with no special expertise in machine learning, it is ...
0
0
0
1
0
0
A Game of Tax Evasion: evidences from an agent-based model
This paper presents a simple agent-based model of an economic system, populated by agents playing different games according to their different view about social cohesion and tax payment. After a first set of simulations, correctly replicating results of existing literature, a wider analysis is presented in order to s...
0
0
0
0
0
1
Variability response functions for statically determinate beams with arbitrary nonlinear constitutive laws
The variability response function (VRF) is generalized to statically determinate Euler Bernoulli beams with arbitrary stress-strain laws following Cauchy elastic behavior. The VRF is a Green's function that maps the spectral density function (SDF) of a statistically homogeneous random field describing the correlation...
0
1
0
0
0
0
Bayesian Uncertainty Estimation for Batch Normalized Deep Networks
We show that training a deep network using batch normalization is equivalent to approximate inference in Bayesian models. We further demonstrate that this finding allows us to make meaningful estimates of the model uncertainty using conventional architectures, without modifications to the network or the training proc...
0
0
0
1
0
0
Multi-Antenna Coded Caching
In this paper we consider a single-cell downlink scenario where a multiple-antenna base station delivers contents to multiple cache-enabled user terminals. Based on the multicasting opportunities provided by the so-called Coded Caching technique, we investigate three delivery approaches. Our baseline scheme employs t...
1
0
1
0
0
0
Convolved subsampling estimation with applications to block bootstrap
The block bootstrap approximates sampling distributions from dependent data by resampling data blocks. A fundamental problem is establishing its consistency for the distribution of a sample mean, as a prototypical statistic. We use a structural relationship with subsampling to characterize the bootstrap in a new and ...
0
0
1
1
0
0
Computing Simple Multiple Zeros of Polynomial Systems
Given a polynomial system f associated with a simple multiple zero x of multiplicity {\mu}, we give a computable lower bound on the minimal distance between the simple multiple zero x and other zeros of f. If x is only given with limited accuracy, we propose a numerical criterion that f is certified to have {\mu} zer...
0
0
1
0
0
0
Latent Geometry and Memorization in Generative Models
It can be difficult to tell whether a trained generative model has learned to generate novel examples or has simply memorized a specific set of outputs. In published work, it is common to attempt to address this visually, for example by displaying a generated example and its nearest neighbor(s) in the training set (i...
1
0
0
1
0
0
Refracting Metasurfaces without Spurious Diffraction
Refraction represents one of the most fundamental operations that may be performed by a metasurface. However, simple phasegradient metasurface designs suffer from restricted angular deflection due to spurious diffraction orders. It has been recently shown, using a circuit-based approach, that refraction without spuri...
0
1
0
0
0
0
Accurate Motion Estimation through Random Sample Aggregated Consensus
We reconsider the classic problem of estimating accurately a 2D transformation from point matches between images containing outliers. RANSAC discriminates outliers by randomly generating minimalistic sampled hypotheses and verifying their consensus over the input data. Its response is based on the single hypothesis t...
1
0
0
0
0
0
Landau Collision Integral Solver with Adaptive Mesh Refinement on Emerging Architectures
The Landau collision integral is an accurate model for the small-angle dominated Coulomb collisions in fusion plasmas. We investigate a high order accurate, fully conservative, finite element discretization of the nonlinear multi-species Landau integral with adaptive mesh refinement using the PETSc library (www.mcs.a...
1
0
0
0
0
0
A Topologist's View of Kinematic Maps and Manipulation Complexity
In this paper we combine a survey of the most important topological properties of kinematic maps that appear in robotics, with the exposition of some basic results regarding the topological complexity of a map. In particular, we discuss mechanical devices that consist of rigid parts connected by joints and show how t...
1
0
1
0
0
0
Faster Tensor Canonicalization
The Butler-Portugal algorithm for obtaining the canonical form of a tensor expression with respect to slot symmetries and dummy-index renaming suffers, in certain cases with a high degree of symmetry, from $O(n!)$ explosion in both computation time and memory. We present a modified algorithm which alleviates this pro...
1
0
0
0
0
0
Mass Preconditioning for the Exact One-Flavor Action in Lattice QCD with Domain-Wall Fermion
The mass-preconditioning (MP) technique has become a standard tool to enhance the efficiency of the hybrid Monte-Carlo simulation (HMC) of lattice QCD with dynamical quarks, for 2-flavors QCD with degenerate quark masses, as well as its extension to the case of one-flavor by taking the square-root of the fermion dete...
0
1
0
0
0
0
Finite-time scaling at the Anderson transition for vibrations in solids
A model in which a three-dimensional elastic medium is represented by a network of identical masses connected by springs of random strengths and allowed to vibrate only along a selected axis of the reference frame, exhibits an Anderson localization transition. To study this transition, we assume that the dynamical ma...
0
1
0
0
0
0
Universal and shape dependent features of surface superconductivity
We analyze the response of a type II superconducting wire to an external magnetic field parallel to it in the framework of Ginzburg-Landau theory. We focus on the surface superconductivity regime of applied field between the second and third critical values, where the superconducting state survives only close to the ...
0
1
1
0
0
0
Weighted Low Rank Approximation for Background Estimation Problems
Classical principal component analysis (PCA) is not robust to the presence of sparse outliers in the data. The use of the $\ell_1$ norm in the Robust PCA (RPCA) method successfully eliminates the weakness of PCA in separating the sparse outliers. In this paper, by sticking a simple weight to the Frobenius norm, we pr...
0
0
1
0
0
0
Controlling Chiral Domain Walls in Antiferromagnets Using Spin-Wave Helicity
In antiferromagnets, the Dzyaloshinskii-Moriya interaction lifts the degeneracy of left- and right-circularly polarized spin waves. This relativistic coupling increases the efficiency of spin-wave-induced domain wall motion and leads to higher drift velocities. We show that in biaxial antiferromagnets, the spin-wave ...
0
1
0
0
0
0
The Spatial Shape of Avalanches
In disordered elastic systems, driven by displacing a parabolic confining potential adiabatically slowly, all advance of the system is in bursts, termed avalanches. Avalanches have a finite extension in time, which is much smaller than the waiting-time between them. Avalanches also have a finite extension $\ell$ in s...
0
1
0
0
0
0
Multiple Topological Electronic Phases in Superconductor MoC
The search for a superconductor with non-s-wave pairing is important not only for understanding unconventional mechanisms of superconductivity but also for finding new types of quasiparticles such as Majorana bound states. Materials with both topological band structure and superconductivity are promising candidates a...
0
1
0
0
0
0
Extension complexity of stable set polytopes of bipartite graphs
The extension complexity $\mathsf{xc}(P)$ of a polytope $P$ is the minimum number of facets of a polytope that affinely projects to $P$. Let $G$ be a bipartite graph with $n$ vertices, $m$ edges, and no isolated vertices. Let $\mathsf{STAB}(G)$ be the convex hull of the stable sets of $G$. It is easy to see that $n \...
1
0
0
0
0
0
Performance Scaling Law for Multi-Cell Multi-User Massive MIMO
This work provides a comprehensive scaling law based performance analysis for multi-cell multi-user massive multiple-input-multiple-output (MIMO) downlink systems. Imperfect channel state information (CSI), pilot contamination, and channel spatial correlation are all considered. First, a sum- rate lower bound is deri...
1
0
0
0
0
0
On the Status of the Measurement Problem: Recalling the Relativistic Transactional Interpretation
In view of a resurgence of concern about the measurement problem, it is pointed out that the Relativistic Transactional Interpretation (RTI) remedies issues previously considered as drawbacks or refutations of the original TI. Specifically, once one takes into account relativistic processes that are not representable...
0
1
0
0
0
0
Pressure-tuning of bond-directional exchange interactions and magnetic frustration in hyperhoneycomb iridate $β$-$\mathrm{Li_2IrO_3}$
We explore the response of Ir $5d$ orbitals to pressure in $\beta$-$\mathrm{Li_2IrO_3}$, a hyperhoneycomb iridate in proximity to a Kitaev quantum spin liquid (QSL) ground state. X-ray absorption spectroscopy reveals a reconstruction of the electronic ground state below 2 GPa, the same pressure range where x-ray magn...
0
1
0
0
0
0
On perpetuities with gamma-like tails
An infinite convergent sum of independent and identically distributed random variables discounted by a multiplicative random walk is called perpetuity, because of a possible actuarial application. We give three disjoint groups of sufficient conditions which ensure that the distribution right tail of a perpetuity $\ma...
0
0
1
0
0
0
Computationally Efficient Estimation of the Spectral Gap of a Markov Chain
We consider the problem of estimating from sample paths the absolute spectral gap $\gamma_*$ of a reversible, irreducible and aperiodic Markov chain $(X_t)_{t \in \mathbb{N}}$ over a finite state $\Omega$. We propose the ${\tt UCPI}$ (Upper Confidence Power Iteration) algorithm for this problem, a low-complexity algo...
0
0
0
1
0
0
Mixed Precision Training of Convolutional Neural Networks using Integer Operations
The state-of-the-art (SOTA) for mixed precision training is dominated by variants of low precision floating point operations, and in particular, FP16 accumulating into FP32 Micikevicius et al. (2017). On the other hand, while a lot of research has also happened in the domain of low and mixed-precision Integer trainin...
1
0
0
0
0
0
Performance of a small size telescope (SST-1M) camera for gamma-ray astronomy with the Cherenkov Telescope Array
The foreseen implementations of the Small Size Telescopes (SST) in CTA will provide unique insights into the highest energy gamma rays offering fundamental means to discover and under- stand the sources populating the Galaxy and our local neighborhood. Aiming at such a goal, the SST-1M is one of the three different i...
0
1
0
0
0
0
Bounded solutions for a class of Hamiltonian systems
We obtain bounded for all $t$ solutions of ordinary differential equations as limits of the solutions of the corresponding Dirichlet problems on $(-L,L)$, with $L \rightarrow \infty$. We derive a priori estimates for the Dirichlet problems, allowing passage to the limit, via a diagonal sequence. This approach carries...
0
0
1
0
0
0
Cosmological perturbation effects on gravitational-wave luminosity distance estimates
Waveforms of gravitational waves provide information about a variety of parameters for the binary system merging. However, standard calculations have been performed assuming a FLRW universe with no perturbations. In reality this assumption should be dropped: we show that the inclusion of cosmological perturbations tr...
0
1
0
0
0
0
Biocompatible Writing of Data into DNA
A simple DNA-based data storage scheme is demonstrated in which information is written using "addressing" oligonucleotides. In contrast to other methods that allow arbitrary code to be stored, the resulting DNA is suitable for downstream enzymatic and biological processing. This capability is crucial for DNA computer...
1
1
0
0
0
0
Faster Clustering via Non-Backtracking Random Walks
This paper presents VEC-NBT, a variation on the unsupervised graph clustering technique VEC, which improves upon the performance of the original algorithm significantly for sparse graphs. VEC employs a novel application of the state-of-the-art word2vec model to embed a graph in Euclidean space via random walks on the...
1
0
0
1
0
0