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We develop a new approach for approximating large independent sets when the input graph is a one-sided spectral expander - that is, the uniform random walk matrix of the graph has its second eigenvalue bounded away from 1. Consequently, we…

Data Structures and Algorithms · Computer Science 2024-11-07 Mitali Bafna , Jun-Ting Hsieh , Pravesh K. Kothari

Given $m \ge 2$ discrete probability distributions over $n$ states each, the minimum-entropy coupling is the minimum-entropy joint distribution whose marginals are the same as the input distributions. Computing the minimum-entropy coupling…

Information Theory · Computer Science 2025-09-30 Spencer Compton

The Matrix-based Renyi's entropy enables us to directly measure information quantities from given data without the costly probability density estimation of underlying distributions, thus has been widely adopted in numerous statistical…

Machine Learning · Statistics 2022-05-17 Yuxin Dong , Tieliang Gong , Shujian Yu , Chen Li

Motivated by recent advances in serverless cloud computing, in particular the "function as a service" (FaaS) model, we consider the problem of minimizing a convex function in a massively parallel fashion, where communication between workers…

Optimization and Control · Mathematics 2024-10-03 Elad Romanov , Fangzhao Zhang , Mert Pilanci

Let us assume that $f$ is a continuous function defined on the unit ball of $\mathbb R^d$, of the form $f(x) = g (A x)$, where $A$ is a $k \times d$ matrix and $g$ is a function of $k$ variables for $k \ll d$. We are given a budget $m \in…

Numerical Analysis · Mathematics 2012-01-18 Massimo Fornasier , Karin Schnass , Jan Vybiral

Estimating the density of a distribution from its samples is a fundamental problem in statistics. Hypothesis selection addresses the setting where, in addition to a sample set, we are given $n$ candidate distributions -- referred to as…

Data Structures and Algorithms · Computer Science 2025-10-23 Maryam Aliakbarpour , Zhan Shi , Ria Stevens , Vincent X. Wang

We examine the properties of distributions with the density of the form: $% \frac{2A_{n}c^{n-2}\sqrt{c^{2}-x^{2}}}{\pi \prod_{j=1}^{n}(c(1+a_{j}^{2})-2a_{j}x)},$ where $c,a_{1},\ldots ,a_{n}$ are some parameters and $A_{n}$ a suitable…

Probability · Mathematics 2019-12-04 Paweł J. Szabłowski

We interpret a class of 4k-dimensional instanton solutions found by Ward, Corrigan, Goddard and Kent as four-dimensional instantons at angles. The superposition of each pair of four-dimensional instantons is associated with four angles…

High Energy Physics - Theory · Physics 2009-10-09 G. Papadopoulos , A. Teschendorff

We propose a class of nonparametric two-sample tests with a cost linear in the sample size. Two tests are given, both based on an ensemble of distances between analytic functions representing each of the distributions. The first test uses…

Machine Learning · Statistics 2015-06-16 Kacper Chwialkowski , Aaditya Ramdas , Dino Sejdinovic , Arthur Gretton

This paper focuses on finding approximate solutions to stochastic optimal control problems with control domains being not necessarily convex, where the state trajectory is subject to controlled stochastic differential equations. The…

Optimization and Control · Mathematics 2025-07-15 Shaolin Ji , Rundong Xu

We use group theoretic methods to calculate the spectrum of short multiplets around the extremum of N=8 gauged supergravity potential which possesses N=2 supersymmetry and SU(3) global symmetry. Upon uplifting to M-theory, it describes a…

High Energy Physics - Theory · Physics 2009-11-13 Igor Klebanov , Thomas Klose , Arvind Murugan

We study a matrix product state (MPS) algorithm to approximate excited states of translationally invariant quantum spin systems with periodic boundary conditions. By means of a momentum eigenstate ansatz generalizing the one of \"Ostlund…

Quantum Physics · Physics 2012-02-06 Bogdan Pirvu , Jutho Haegeman , Frank Verstraete

We present a new $4$-approximation algorithm for the Combinatorial Motion Planning problem which runs in $\mathcal{O}(n^2\alpha(n^2,n))$ time, where $\alpha$ is the functional inverse of the Ackermann function, and a fully distributed…

Discrete Mathematics · Computer Science 2018-05-24 Simran Dokania , Aditya Paliwal , Shrisha Rao

The metric sketching problem is defined as follows. Given a metric on $n$ points, and $\epsilon>0$, we wish to produce a small size data structure (sketch) that, given any pair of point indices, recovers the distance between the points up…

Computational Geometry · Computer Science 2016-11-30 Piotr Indyk , Tal Wagner

We (claim to) prove the extremely surprising fact that NP=RP. It is achieved by creating a Fully Polynomial-Time Randomized Approximation Scheme (FPRAS) for approximately counting the number of independent sets in bounded degree graphs,…

Computational Complexity · Computer Science 2020-08-06 András Faragó

We prove that, unless P=NP, there is no polynomial-time algorithm to approximate within some multiplicative constant the average size of an independent set in graphs of maximum degree 6. This is a special case of a more general result for…

Computational Complexity · Computer Science 2021-07-20 Andreas Galanis , Daniel Stefankovic , Eric Vigoda

Frequency estimation in data streams is one of the classical problems in streaming algorithms. Following much research, there are now almost matching upper and lower bounds for the trade-off needed between the number of samples and the…

Computational Complexity · Computer Science 2023-01-16 Shachar Lovett , Jiapeng Zhang

Motivated by a problem arising when analysing data from quarantine searches, we explore properties of distributions of sums of independent means of independent lattice-valued random variables. The aim is to determine the extent to which…

Statistics Theory · Mathematics 2013-10-01 Geoffrey Decrouez , Peter Hall

Many scientific and engineering problems require to perform Bayesian inferences in function spaces, in which the unknowns are of infinite dimension. In such problems, many standard Markov Chain Monte Carlo (MCMC) algorithms become arbitrary…

Numerical Analysis · Mathematics 2016-04-12 Zhe Feng , Jinglai Li

Assume that one observes the $k$th, $2k$th$,\ldots,nk$th value of a Markov chain $X_{1,h},\ldots,X_{nk,h}$. That means we assume that a high frequency Markov chain runs in the background on a very fine time grid but that it is only observed…

Statistics Theory · Mathematics 2014-03-17 Valentin Konakov , Enno Mammen , Jeannette Woerner