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Related papers: Upper Bounds on the Size of Grain-Correcting Codes

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Non-binary codes correcting multiple deletions have recently attracted a lot of attention. In this work, we focus on multiplicity-free codes, a family of non-binary codes where all symbols are distinct. Our main contribution is a new…

Information Theory · Computer Science 2025-08-06 Michael Schaller , Beatrice Toesca , Van Khu Vu

This paper investigates the theory of sum-rank metric codes for which the individual matrix blocks may have different sizes. Various bounds on the cardinality of a code are derived, along with their asymptotic extensions. The duality theory…

Information Theory · Computer Science 2020-10-07 Eimear Byrne , Heide Gluesing-Luerssen , Alberto Ravagnani

We consider multidimensional codes capable of correcting a burst error of weight at most $2$. When two positions are in error, the burst limits their relative position. We study three such limitations: the $L_\infty$ distance between the…

Information Theory · Computer Science 2025-10-30 Hagai Berend , Ohad Elishco , Moshe Schwartz

This paper considers the performance of Reed-Muller (RM) codes transmitted over binary memoryless symmetric (BMS) channels under bitwise maximum-a-posteriori (bit-MAP) decoding. Its main result is that, for a fixed BMS channel, the family…

Information Theory · Computer Science 2023-06-14 Galen Reeves , Henry D. Pfister

Locally repairable codes (LRCs) were originally introduced to enable efficient recovery from erasures in distributed storage systems by accessing only a small number of other symbols. While their structural properties-such as bounds and…

Information Theory · Computer Science 2026-02-23 Hoang Ly , Emina Soljanin , Philip Whiting

Subspace codes and rank-metric codes can be used to correct errors and erasures in network, with linear network coding. Subspace codes were introduced by Koetter and Kschischang to correct errors and erasures in networks where topology is…

Information Theory · Computer Science 2012-02-07 Hessam Mahdavifar , Alexander Vardy

The foundational concept of Max-Margin in machine learning is ill-posed for output spaces with more than two labels such as in structured prediction. In this paper, we show that the Max-Margin loss can only be consistent to the…

Machine Learning · Computer Science 2022-03-22 Alex Nowak-Vila , Alessandro Rudi , Francis Bach

In this note we show that the methods of Motohashi and Meurman yield the same upper bound on the error term in the binary additive divisor problem. With this goal, we improve an estimate in the proof of Motohashi.

Number Theory · Mathematics 2016-12-06 Olga Balkanova , Dmitry Frolenkov

Motivated by a wide-spread use of convex optimization techniques, convexity properties of bit error rate of the maximum likelihood detector operating in the AWGN channel are studied for arbitrary constellations and bit mappings, which also…

Information Theory · Computer Science 2010-04-16 Sergey Loyka , Francois Gagnon , Victoria Kostina

We develop upper bounds on code size for an independent and identically distributed deletion and insertion channels for a given code length and target frame error probability. The bounds are obtained as a variation of a general converse…

Information Theory · Computer Science 2026-04-14 Ruslan Morozov , Tolga Mete Duman

Binary classification involves predicting the label of an instance based on whether the model score for the positive class exceeds a threshold chosen based on the application requirements (e.g., maximizing recall for a precision bound).…

Machine Learning · Computer Science 2023-11-21 Gundeep Arora , Srujana Merugu , Anoop Saladi , Rajeev Rastogi

Quantum error mitigation is a promising route to achieving quantum utility, and potentially quantum advantage in the near-term. Many state-of-the-art error mitigation schemes use knowledge of the errors in the quantum processor, which opens…

In this work we present some results that allow to improve the decoding radius in solving polynomial linear systems with errors in the scenario where errors are additive and randomly distributed over a finite field. The decoding radius…

Information Theory · Computer Science 2020-03-05 Eleonora Guerrini , Romain Lebreton , Ilaria Zappatore

We consider linear codes over a field in which the error values are restricted to a subgroup of its unit group. This scenario captures Lee distance codes as well as codes over the Gaussian or Eisenstein integers. Codes correcting restricted…

Information Theory · Computer Science 2026-01-21 Jens Zumbrägel

The problem of establishing out-of-sample bounds for the values of an unkonwn ground-truth function is considered. Kernels and their associated Hilbert spaces are the main formalism employed herein along with an observational model where…

Machine Learning · Computer Science 2022-09-13 Paul Scharnhorst , Emilio T. Maddalena , Yuning Jiang , Colin N. Jones

This paper investigates the phenomenon of benign overfitting in binary classification problems with heavy-tailed input distributions, extending the analysis of maximum margin classifiers to $\alpha$ sub-exponential distributions ($\alpha…

Machine Learning · Computer Science 2024-10-17 Kota Okudo , Kei Kobayashi

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 prove a new lower bound on the field size of locally repairable codes (LRCs). Additionally, we construct maximally recoverable (MR) codes which are cyclic. While a known construction for MR codes has the same parameters, it produces…

Information Theory · Computer Science 2022-08-23 Han Cai , Moshe Schwartz

Maximum-likelihood (ML) decoding can be used to obtain the optimal performance of error correction codes. However, the size of the search space and consequently the decoding complexity grows exponentially, making it impractical to be…

Information Theory · Computer Science 2022-05-25 Mohammad Rowshan , Jinhong Yuan

A linear bubble model of grain growth is introduced to study the conditions under which an isolated grain can grow to a size much larger than the surrounding matrix average (abnormal growth). We first consider the case of bubbles of two…

Materials Science · Physics 2007-05-23 W. W. Mullins , Jorge Vinals