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We consider linear codes over a finite field of odd characteristic, derived from determinantal varieties, obtained from symmetric matrices of bounded ranks. A formula for the weight of a code word is derived. Using this formula, we have…

Information Theory · Computer Science 2023-12-25 Peter Beelen , Trygve Johnsen , Prasant Singh

Low-rank approximations, of the weight and feature space can enhance the performance of deep learning models, whether in terms of improving generalization or reducing the latency of inference. However, there is no clear consensus yet on…

Computation and Language · Computer Science 2024-05-24 Arnav Chavan , Nahush Lele , Deepak Gupta

Symmetric functions, which take as input an unordered, fixed-size set, are known to be universally representable by neural networks that enforce permutation invariance. These architectures only give guarantees for fixed input sizes, yet in…

Machine Learning · Computer Science 2022-10-11 Aaron Zweig , Joan Bruna

Coding in the projective space has received recently a lot of attention due to its application in network coding. Reduced row echelon form of the linear subspaces and Ferrers diagram can play a key role for solving coding problems in the…

Information Theory · Computer Science 2009-03-14 Tuvi Etzion , Natalia Silberstein

We investigate two fundamental questions intersecting coding theory and combinatorial geometry, with emphasis on their connections. These are the problem of computing the asymptotic density of MRD codes in the rank metric, and the Critical…

Combinatorics · Mathematics 2022-01-19 Anina Gruica , Alberto Ravagnani , John Sheekey , Ferdinando Zullo

In this paper we consider a Metzner-Kapturowski-like decoding algorithm for high-order interleaved sum-rank-metric codes, offering a novel perspective on the decoding process through the concept of an error code. The error code, defined as…

Information Theory · Computer Science 2024-09-30 Thomas Jerkovits , Felicitas Hörmann , Hannes Bartz

Two-weight linear codes are linear codes in which any nonzero codeword can have only two possible distinct weights. Those in the Hamming metric have proven to be very interesting for their connections with authentication codes, association…

Information Theory · Computer Science 2024-05-07 Ferdinando Zullo , Olga Polverino , Paolo Santonastaso , John Sheekey

Low rank approximation is an important tool used in many applications of signal processing and machine learning. Recently, randomized sketching algorithms were proposed to effectively construct low rank approximations and obtain approximate…

Information Theory · Computer Science 2018-09-11 Shashanka Ubaru , Arya Mazumdar , Yousef Saad

In this work, linearized multivariate skew polynomials over division rings are introduced. Such polynomials are right linear over the corresponding centralizer and generalize linearized polynomial rings over finite fields, group rings or…

Rings and Algebras · Mathematics 2021-12-07 Umberto Martínez-Peñas

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

We introduce the class of partition-balanced families of codes, and show how to exploit their combinatorial invariants to obtain upper and lower bounds on the number of codes that have a prescribed property. In particular, we derive precise…

Information Theory · Computer Science 2018-12-13 Eimear Byrne , Alberto Ravagnani

Binary codes have been widely used in vision problems as a compact feature representation to achieve both space and time advantages. Various methods have been proposed to learn data-dependent hash functions which map a feature vector to a…

Computer Vision and Pattern Recognition · Computer Science 2014-10-22 Jie Feng , Wei Liu , Yan Wang

The substantial computational demands of modern large-scale deep learning present significant challenges for efficient training and deployment. Recent research has revealed a widespread phenomenon wherein deep networks inherently learn…

Machine Learning · Computer Science 2026-02-04 Laura Balzano , Tianjiao Ding , Benjamin D. Haeffele , Soo Min Kwon , Qing Qu , Peng Wang , Zhangyang Wang , Can Yaras

This paper examines linear binary codes capable of correcting one or more errors. For the single-error-correcting case, it is shown that the Hamming bound is achieved by a constructive method, and an exact expression for the minimal…

Information Theory · Computer Science 2025-12-16 Timofei Izhitskii

While deep learning is successful in a number of applications, it is not yet well understood theoretically. A satisfactory theoretical characterization of deep learning however, is beginning to emerge. It covers the following questions: 1)…

Machine Learning · Computer Science 2019-08-27 Tomaso Poggio , Andrzej Banburski , Qianli Liao

Skew polynomial rings provide a fundamental example of noncommutative principal ideal domains. Special quotients of these rings yield matrix algebras that play a central role in the theory of rank-metric codes. Recent breakthroughs have…

Information Theory · Computer Science 2025-11-10 José Gómez-Torrecillas , F. J. Lobillo , Gabriel Navarro , Paolo Santonastaso

The important problem of weighted sum rate maximization (WSRM) in a multicellular environment is intrinsically sensitive to channel estimation errors. In this paper, we study ways to maximize the weighted sum rate in a linearly precoded…

Information Theory · Computer Science 2013-10-21 Muhammad Fainan Hanif , Le-Nam Tran , Antti Tölli , Markku Juntti , Savo Glisic

Recently, codes in the sum-rank metric attracted attention due to several applications in e.g. multishot network coding, distributed storage and quantum-resistant cryptography. The sum-rank analogs of Reed-Solomon and Gabidulin codes are…

Information Theory · Computer Science 2022-09-07 Felicitas Hörmann , Hannes Bartz

In this paper, we have introduced the concepts of support distribution and the support enumerator as refinements of the classical weight distribution and weight enumerator respectively, capturing coordinate level activity in linear block…

Information Theory · Computer Science 2026-01-14 Nitin Kenjale , Anuradha S. Garge

Error-correcting codes over the real field are studied which can locate outlying computational errors when performing approximate computing of real vector--matrix multiplication on resistive crossbars. Prior work has concentrated on…

Information Theory · Computer Science 2024-02-22 Hengjia Wei , Ron M. Roth