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In this paper, we establish the list-decoding capacity theorem for sum-rank metric codes. This theorem implies the list-decodability theorem for random general sum-rank metric codes: Any random general sum-rank metric code with a rate not…

Information Theory · Computer Science 2025-03-14 Yang Liu , Anna Baumeister , Antonia Wachter-Zeh

Random instances of constraint satisfaction problems such as k-SAT provide challenging benchmarks. If there are m constraints over n variables there is typically a large range of densities r=m/n where solutions are known to exist with…

Discrete Mathematics · Computer Science 2009-11-13 Amin Coja-Oghlan

In $K$-means classification, a set of data will form clusters, i.e. classes, if the measured distances between data points (or some common point in each class) are below a certain threshold. With the assumption that the data points are…

Probability · Mathematics 2016-02-12 Robert A. Murphy

This paper presents an achievability bound that evaluates the exact probability of error of an ensemble of random codes that are decoded by a minimum distance decoder. Compared to the state-of-the-art which demands exponential computation…

Information Theory · Computer Science 2023-05-17 Ioannis Papoutsidakis , Angela Doufexi , Robert J. Piechocki

In stochastic geometry there are several instances of threshold phenomena in high dimensions: the behavior of a limit of some expectation changes abruptly when some parameter passes through a critical value. This note continues the…

Probability · Mathematics 2021-03-23 Daniel Hug , Rolf Schneider

A code over a finite alphabet is called locally recoverable (LRC) if every symbol in the encoding is a function of a small number (at most $r$) other symbols. We present a family of LRC codes that attain the maximum possible value of the…

Information Theory · Computer Science 2014-07-14 Itzhak Tamo , Alexander Barg

In this paper we introduce a new model of random simplicial complexes depending on multiple probability parameters. This model includes the well-known Linial - Meshulam random simplicial complexes and random clique complexes as special…

Algebraic Topology · Mathematics 2015-03-03 A. Costa , M. Farber

The classical zero-one law for first-order logic on random graphs says that for any first-order sentence $\phi$ in the theory of graphs, as n approaches infinity, the probability that the random graph G(n, p) satisfies $\phi$ approaches…

Combinatorics · Mathematics 2009-04-17 Phokion G. Kolaitis , Swastik Kopparty

In this work, we introduce a notion of reachability entropy to characterize the smallest data rate which is sufficient enough to enforce reach-while-stay specification. We also define data rates of coder-controllers that can enforce this…

Optimization and Control · Mathematics 2022-06-22 Mahendra Singh Tomar , Majid Zamani

The need to condition distributional properties such as expectation, variance, and entropy arises in algorithmic fairness, model simplification, robustness and many other areas. At face value however, distributional properties are not…

Programming Languages · Computer Science 2019-03-27 Zenna Tavares , Xin Zhang , Edgar Minaysan , Javier Burroni , Rajesh Ranganath , Armando Solar Lezama

This paper studies the parameters for which Reed-Muller (RM) codes over $GF(2)$ can correct random erasures and random errors with high probability, and in particular when can they achieve capacity for these two classical channels.…

Information Theory · Computer Science 2014-11-18 Emmanuel Abbe , Amir Shpilka , Avi Wigderson

For two correlated graphs which are independently sub-sampled from a common Erd\H{o}s-R\'enyi graph $\mathbf{G}(n, p)$, we wish to recover their \emph{latent} vertex matching from the observation of these two graphs \emph{without labels}.…

Statistics Theory · Mathematics 2022-05-31 Jian Ding , Hang Du

Given F:[a,b]^k\to [a,b] and a nonconstant X_0 with P(X_0\in [a,b])=1, define the hierarchical sequence of random variables {X_n}_{n\ge 0} by X_{n+1}=F(X_{n,1},...,X_{n,k}), where X_{n,i} are i.i.d. as X_n. Such sequences arise from…

Probability · Mathematics 2007-05-23 Larry Goldstein

The spectra of random feature matrices provide essential information on the conditioning of the linear system used in random feature regression problems and are thus connected to the consistency and generalization of random feature models.…

Machine Learning · Statistics 2022-12-13 Zhijun Chen , Hayden Schaeffer , Rachel Ward

Assigning significance in high-dimensional regression is challenging. Most computationally efficient selection algorithms cannot guard against inclusion of noise variables. Asymptotically valid p-values are not available. An exception is a…

Methodology · Statistics 2009-06-12 Nicolai Meinshausen , Lukas Meier , Peter Bühlmann

It has recently been observed that certain extremely simple feature encoding techniques are able to achieve state of the art performance on several standard image classification benchmarks including deep belief networks, convolutional nets,…

Machine Learning · Computer Science 2013-01-08 Misha Denil , Nando de Freitas

We study occurrences of patterns on clusters of size n in random fields on Z^d. We prove that for a given pattern, there is a constant a>0 such that the probability that this pattern occurs at most an times on a cluster of size n is…

Probability · Mathematics 2008-03-13 Remco van der Hofstad , Wouter Kager

The problem of CSP sparsification asks: for a given CSP instance, what is the sparsest possible reweighting such that for every possible assignment to the instance, the number of satisfied constraints is preserved up to a factor of $1 \pm…

Data Structures and Algorithms · Computer Science 2026-02-12 Joshua Brakensiek , Venkatesan Guruswami , Aaron Putterman

An efficient algorithm is presented to compute the characteristic polynomial of a threshold graph. Threshold graphs were introduced by Chv\'atal and Hammer, as well as by Henderson and Zalcstein in 1977. A threshold graph is obtained from a…

Data Structures and Algorithms · Computer Science 2015-03-03 Martin Fürer

A collection of sets satisfies a $(\delta,\varepsilon)$-proximity gap with respect to some property if for every set in the collection, either (i) all members of the set are $\delta$-close to the property in (relative) Hamming distance, or…

Information Theory · Computer Science 2026-01-16 Fernando Granha Jeronimo , Lenny Liu , Pranav Rajpal
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