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We derive a linear programming bound on the maximum cardinality of error-correcting codes in the sum-rank metric. Based on computational experiments on relatively small instances, we observe that the obtained bounds outperform all…

Combinatorics · Mathematics 2024-06-25 Aida Abiad , Alexander L. Gavrilyuk , Antonina P. Khramova , Ilia Ponomarenko

We study the notion of a generalization bound being uniformly tight, meaning that the difference between the bound and the population loss is small for all learning algorithms and all population distributions. Numerous generalization bounds…

Machine Learning · Computer Science 2023-11-29 Michael Gastpar , Ido Nachum , Jonathan Shafer , Thomas Weinberger

A classic result in algorithmic information theory is that every infinite binary sequence is computable from a Martin-Loef random infinite binary sequence. Proved independently by Kucera and Gacs, this result answered a question by Charles…

Computational Complexity · Computer Science 2017-06-13 George Barmpalias , Andrew Lewis-Pye

New bounds on classification error rates for the error-correcting output code (ECOC) approach in machine learning are presented. These bounds have exponential decay complexity with respect to codeword length and theoretically validate the…

Machine Learning · Computer Science 2021-09-21 Hieu D. Nguyen , Mohammed Sarosh Khan , Nicholas Kaegi , Shen-Shyang Ho , Jonathan Moore , Logan Borys , Lucas Lavalva

We address the problem of bounding below the probability of error under maximum likelihood decoding of a binary code with a known distance distribution used on a binary symmetric channel. An improved upper bound is given for the maximum…

Information Theory · Computer Science 2007-07-16 Alexander Barg , Andrew McGregor

The classical coding theorem in Kolmogorov complexity states that if an $n$-bit string $x$ is sampled with probability $\delta$ by an algorithm with prefix-free domain then K$(x) \leq \log(1/\delta) + O(1)$. In a recent work, Lu and…

Computational Complexity · Computer Science 2022-04-19 Zhenjian Lu , Igor C. Oliveira , Marius Zimand

In this work, a new upper bound for average error probability of a two-user discrete memoryless (DM) multiple-access channel (MAC) is derived. This bound can be universally obtained for all discrete memoryless MACs with given input and…

Information Theory · Computer Science 2009-01-09 Ali Nazari , Achilleas Anastasopoulos , S. Sandeep Pradhan

We present a new model for LT codes which simplifies the analysis of the error probability of decoding by belief propagation. For any given degree distribution, we provide the first rigorous expression for the limiting error probability as…

Information Theory · Computer Science 2007-07-13 Elitza N. Maneva , Amin Shokrollahi

By a locally recoverable code (LRC), we will in this paper, mean a linear code in which a given code symbol can be recovered by taking a linear combination of at most $r$ other code symbols with $r << k$. A natural extension is to the local…

Information Theory · Computer Science 2018-12-07 S. B. Balaji , Ganesh R. Kini , P. Vijay Kumar

We consider the lossless compression bound of any individual data sequence. If we fit the data by a parametric model, the entropy quantity $nH({\hat \theta}_n)$ obtained by plugging in the maximum likelihood estimate is an underestimate of…

Information Theory · Computer Science 2024-01-23 Lei M Li

Since the classical work of Berlekamp, McEliece and van Tilborg, it is well known that the problem of exact maximum-likelihood (ML) decoding of general linear codes is NP-hard. In this paper, we show that exact ML decoding of a classs of…

Information Theory · Computer Science 2016-11-17 Weiyu Xu , Babak Hassibi

We analyze the list-decodability, and related notions, of random linear codes. This has been studied extensively before: there are many different parameter regimes and many different variants. Previous works have used complementary styles…

Information Theory · Computer Science 2017-04-11 Atri Rudra , Mary Wootters

This paper shows that, with high probability, randomly punctured Reed-Solomon codes over fields of polynomial size achieve the list decoding capacity. More specifically, we prove that for any $\epsilon>0$ and $R\in (0,1)$, with high…

Information Theory · Computer Science 2025-09-03 Zeyu Guo , Zihan Zhang

This work addresses the question of achieving capacity with lattice codes in multi-antenna block fading channels when the number of fading blocks tends to infinity. A design criterion based on the normalized minimum determinant is proposed…

Information Theory · Computer Science 2015-07-28 Laura Luzzi , Roope Vehkalahti

We study the bias of random bounded-degree polynomials over odd prime fields and show that, with probability exponentially close to 1, such polynomials have exponentially small bias. This also yields an exponential tail bound on the weight…

Discrete Mathematics · Computer Science 2018-06-20 Paul Beame , Shayan Oveis Gharan , Xin Yang

A well-known technique in estimating probabilities of rare events in general and in information theory in particular (used, e.g., in the sphere-packing bound), is that of finding a reference probability measure under which the event of…

Information Theory · Computer Science 2014-12-23 Rami Atar , Neri Merhav

For a broad class of input-output maps, arguments based on the coding theorem from algorithmic information theory (AIT) predict that simple (low Kolmogorov complexity) outputs are exponentially more likely to occur upon uniform random…

Data Analysis, Statistics and Probability · Physics 2019-10-03 Kamaludin Dingle , Guillermo Valle Pérez , Ard A. Louis

In this paper, we prove the existence of capacity achieving linear codes with random binary sparse generating matrices. The results on the existence of capacity achieving linear codes in the literature are limited to the random binary codes…

Information Theory · Computer Science 2011-08-31 A. Makhdoumi Kakhaki , H. Karkeh Abadi , P. Pad , H. Saeedi , F. Marvasti , K. Alishahi

Several types of AL-FEC (Application-Level FEC) codes for the Packet Erasure Channel exist. Random Linear Codes (RLC), where redundancy packets consist of random linear combinations of source packets over a certain finite field, are a…

Information Theory · Computer Science 2014-08-26 Kazuhisa Matsuzono , Vincent Roca , Hitoshi Asaeda

In this paper, we study the hardness of decoding a random code endowed with the cover metric. As the cover metric lies in between the Hamming and rank metric, it presents itself as a promising candidate for code-based cryptography. We give…

Information Theory · Computer Science 2022-05-26 Sebastian Bitzer , Julian Renner , Antonia Wachter-Zeh , Violetta Weger
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