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We consider the problem of sparse coding, where each sample consists of a sparse linear combination of a set of dictionary atoms, and the task is to learn both the dictionary elements and the mixing coefficients. Alternating minimization is…

Machine Learning · Computer Science 2014-07-30 Alekh Agarwal , Animashree Anandkumar , Prateek Jain , Praneeth Netrapalli

We show that the typical coordinate-wise encoding of multivariate ergodic source into prescribed alphabets has the entropy profile close to the convolution of the entropy profile of the source and the modular polymatroid that is determined…

Information Theory · Computer Science 2020-04-23 Michal Kupsa

We address the problem of searching for a change point in an anomalous process among a finite set of M processes. Specifically, we address a composite hypothesis model in which each process generates measurements following a common…

Machine Learning · Statistics 2024-12-30 Liad Lea Didi , Tomer Gafni , Kobi Cohen

We consider optimal stopping problems, in which a sequence of independent random variables is drawn from a known continuous density. The objective of such problems is to find a procedure which maximizes the expected reward; this is often…

Probability · Mathematics 2020-12-07 Hugh Entwistle , Christopher Lustri , Georgy Sofronov

We introduce a universal quantization scheme based on random coding, and we analyze its performance. This scheme consists of a source-independent random codebook (typically_mismatched_ to the source distribution), followed by optimal…

Information Theory · Computer Science 2007-07-13 Ioannis Kontoyiannis , Rami Zamir

Let $P = \{p(i)\}$ be a measure of strictly positive probabilities on the set of nonnegative integers. Although the countable number of inputs prevents usage of the Huffman algorithm, there are nontrivial $P$ for which known methods find a…

Information Theory · Computer Science 2007-07-13 Michael B. Baer

We introduce a simple and efficient algorithm for stochastic linear bandits with finitely many actions that is asymptotically optimal and (nearly) worst-case optimal in finite time. The approach is based on the frequentist…

Machine Learning · Statistics 2021-07-05 Johannes Kirschner , Tor Lattimore , Claire Vernade , Csaba Szepesvári

We extend the data compression theorem to the case of ergodic quantum information sources. Moreover, we provide an asymptotically optimal compression scheme which is based on the concept of high probability subspaces. The rate of this…

Quantum Physics · Physics 2007-05-23 Igor Bjelakovic , Arleta Szkola

When treating Markov decision processes (MDPs) with large state spaces, using explicit representations quickly becomes unfeasible. Lately, Wimmer et al. have proposed a so-called symblicit algorithm for the synthesis of optimal strategies…

Logic in Computer Science · Computer Science 2014-07-22 Aaron Bohy , Véronique Bruyère , Jean-François Raskin

The rate-distortion saddle-point problem considered by Lapidoth (1997) consists in finding the minimum rate to compress an arbitrary ergodic source when one is constrained to use a random Gaussian codebook and minimum (Euclidean) distance…

Information Theory · Computer Science 2018-09-03 Lin Zhou , Vincent Y. F. Tan , Mehul Motani

In this paper, we study the problem of estimating a Markov chain $X$(signal) from its noisy partial information $Y$, when the transition probability kernel depends on some unknown parameters. Our goal is to compute the conditional…

Probability · Mathematics 2007-05-23 Anastasia Papavasiliou

Universal fixed-to-variable lossless source coding for memoryless sources is studied in the finite blocklength and higher-order asymptotics regimes. Optimal third-order coding rates are derived for general fixed-to-variable codes and for…

Information Theory · Computer Science 2014-12-16 Oliver Kosut , Lalitha Sankar

In this paper will be presented new approach to entropy coding: family of generalizations of standard numeral systems which are optimal for encoding sequence of equiprobable symbols, into asymmetric numeral systems - optimal for freely…

Information Theory · Computer Science 2009-05-21 Jarek Duda

When treating Markov decision processes (MDPs) with large state spaces, using explicit representations quickly becomes unfeasible. Lately, Wimmer et al. have proposed a so-called symblicit algorithm for the synthesis of optimal strategies…

Data Structures and Algorithms · Computer Science 2014-06-23 Aaron Bohy , Véronique Bruyère , Jean-François Raskin

The use of parity-check gates in information theory has proved to be very efficient. In particular, error correcting codes based on parity checks over low-density graphs show excellent performances. Another basic issue of information…

Disordered Systems and Neural Networks · Physics 2007-05-23 S. Ciliberti , M. Mezard , R. Zecchina

We study the problem of compressing a source sequence in the presence of side-information that is related to the source via insertions, deletions and substitutions. We propose a simple algorithm to compress the source sequence when the…

Information Theory · Computer Science 2016-11-15 Nan Ma , Kannan Ramchandran , David Tse

We investigate how to measure and define the entropy of a simple chaotic system, three hard spheres on a ring. A novel approach is presented, which does not assume the ergodic hypothesis. It consists of transforming the particles collision…

Computational Physics · Physics 2023-05-08 Matej Vedak , Graeme J Ackland

We investigate the behavior of the periods and border lengths of random words over a fixed alphabet. We show that the asymptotic probability that a random word has a given maximal border length $k$ is a constant, depending only on $k$ and…

Formal Languages and Automata Theory · Computer Science 2019-12-18 Štěpán Holub , Jeffrey Shallit

This paper proposes a novel entropy encoding technique for lossless data compression. Representing a message string by its lexicographic index in the permutations of its symbols results in a compressed version matching Shannon entropy of…

Information Theory · Computer Science 2017-03-24 Abu Bakar Siddique

A lossy source code $\mathcal{C}$ with rate $R$ for a discrete memoryless source $S$ is called subset-universal if for every $0<R'< R$, almost every subset of $2^{nR'}$ of its codewords achieves average distortion close to the source's…

Information Theory · Computer Science 2015-03-13 Or Ordentlich , Ofer Shayevitz