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In this paper, we propose a novel learning-aided sphere decoding (SD) scheme for large multiple-input--multiple-output systems, namely, deep path prediction-based sphere decoding (DPP-SD). In this scheme, we employ a neural network (NN) to…

Information Theory · Computer Science 2020-01-03 Doyeon Weon , Kyungchun Lee

Recently, a new method for encoding data sets in the form of "Density Codes" was proposed in the literature (Courrieu, 2006). This method allows to compare sets of points belonging to every multidimensional space, and to build shape spaces…

Neural and Evolutionary Computing · Computer Science 2008-06-25 Pierre Courrieu

Fast SC decoding overcomes the latency caused by the serial nature of the SC decoding by identifying new nodes in the upper levels of the SC decoding tree and implementing their fast parallel decoders. In this work, we first present a novel…

We propose new results on low weight codewords of affine and projective generalized Reed-Muller codes. In the affine case we prove that if the size of the working finite field is large compared to the degree of the code, the low weight…

Information Theory · Computer Science 2013-04-09 Stéphane Ballet , Robert Rolland

Neural machine translation models rely on the beam search algorithm for decoding. In practice, we found that the quality of hypotheses in the search space is negatively affected owing to the fixed beam size. To mitigate this problem, we…

Computation and Language · Computer Science 2017-07-11 Raphael Shu , Hideki Nakayama

Qudit toric codes are a natural higher-dimensional generalization of the well-studied qubit toric code. However standard methods for error correction of the qubit toric code are not applicable to them. Novel decoders are needed. In this…

Quantum Physics · Physics 2014-06-19 Hussain Anwar , Benjamin J. Brown , Earl T. Campbell , Dan E. Browne

The state-of-the-art error correcting codes are based on large random constructions (random graphs, random permutations, ...) and are decoded by linear-time iterative algorithms. Because of these features, they are remarkable examples of…

Disordered Systems and Neural Networks · Physics 2016-08-31 Silvio Franz , Michele Leone , Andrea Montanari , Federico Ricci-Tersenghi

We study spatially coupled LDPC codes that allow access to sub-blocks much smaller than the full code block. Sub-block access is realized by a semi-global decoder that decodes a chosen target sub-block by only accessing the target, plus a…

Information Theory · Computer Science 2020-10-22 Eshed Ram , Yuval Cassuto

This paper studies two crucial problems in the context of coded distributed storage systems directly related to their performance: 1) for a fixed alphabet size, determine the minimum number of servers the system must have for its service…

Information Theory · Computer Science 2024-07-02 Altan B. Kilic , Alberto Ravagnani , Emina Soljanin

A set of linearly constrained permutation matrices are proposed for constructing a class of permutation codes. Making use of linear constraints imposed on the permutation matrices, we can formulate a minimum Euclidian distance decoding…

Information Theory · Computer Science 2015-03-17 Tadashi Wadayama , Manabu Hagiwara

Speculative Decoding (SD) ensures that the output matches the target model's distribution exactly. However, we argue that this distribution matching requirement is too stringent and results in unnecessarily low acceptance rates, limiting…

Transformer language models generate text autoregressively, making inference latency proportional to the number of tokens generated. Speculative decoding reduces this latency without sacrificing output quality, by leveraging a small draft…

Machine Learning · Computer Science 2025-10-24 Clara Mohri , Haim Kaplan , Tal Schuster , Yishay Mansour , Amir Globerson

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

The training complexity of deep learning-based channel decoders scales exponentially with the codebook size and therefore with the number of information bits. Thus, neural network decoding (NND) is currently only feasible for very short…

Information Theory · Computer Science 2017-02-23 Sebastian Cammerer , Tobias Gruber , Jakob Hoydis , Stephan ten Brink

Recently, image-to-image translation research has witnessed remarkable progress. Although current approaches successfully generate diverse outputs or perform scalable image transfer, these properties have not been combined into a single…

Computer Vision and Pattern Recognition · Computer Science 2019-08-20 Yaxing Wang , Abel Gonzalez-Garcia , Joost van de Weijer , Luis Herranz

Codes in finite projective spaces equipped with the subspace distance have been proposed for error control in random linear network coding. Here we collect the present knowledge on lower and upper bounds for binary subspace codes for…

Combinatorics · Mathematics 2018-10-01 Daniel Heinlein , Sascha Kurz

We examine in detail the accuracy, efficiency and implementation issues that arise when a simplified code structure is employed to evaluate the partition function of the two-dimensional square Ising model on periodic lattices though…

Statistical Mechanics · Physics 2020-01-03 David Yevick , Jesse Thompson

Our main technical result is that, in the coset leader graph of a linear binary code of block length n, the metric balls spanned by constant-weight vectors grow exponentially slower than those in $\{0,1\}^n$. Following the approach of…

Information Theory · Computer Science 2014-12-17 Eran Iceland , Alex Samorodnitsky

In this work, we consider adaptive linear programming (ALP) decoding of linear codes over the finite field $\mathbb{F}_p$ of size $p$ where $p$ is a prime. In particular, we provide a general construction of valid inequalities for the…

Information Theory · Computer Science 2019-11-20 Eirik Rosnes , Michael Helmling

The union-find decoder is a leading algorithmic approach to the correction of quantum errors on the surface code, achieving code thresholds comparable to minimum-weight perfect matching (MWPM) with amortised computational time scaling…

Quantum Physics · Physics 2025-04-10 Sam J. Griffiths , Dan E. Browne