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Random linear codes are a workhorse in coding theory, and are used to show the existence of codes with the best known or even near-optimal trade-offs in many noise models. However, they have little structure besides linearity, and are not…

Computational Complexity · Computer Science 2024-07-11 Venkatesan Guruswami , Jonathan Mosheiff

In the torn paper channel, a transmitted codeword is broken at random locations into fragments that arrive at the decoder in an unordered manner. A central theoretical challenge within this model is global alignment -- the task of…

Information Theory · Computer Science 2026-05-25 Junsheng Liu , Netanel Raviv

Undetected errors are important for linear codes, which are the only type of errors after hard decision and automatic-repeat-request (ARQ), but do not receive much attention on their correction. In concatenated channel coding, suboptimal…

Information Theory · Computer Science 2019-01-09 Jingzhao Wang , Yuan Luo

The successive cancellation list decoder (SCL) is an efficient decoder for classical polar codes with low decoding error, approximating the maximum likelihood decoder (MLD) for small list sizes. Here we adapt the SCL to the task of decoding…

Quantum Physics · Physics 2026-05-14 Anqi Gong , Joseph M. Renes

With the current increase in the data produced by the Large Hadron Collider (LHC) at CERN, it becomes important to process this data in a corresponding manner. To begin with, to efficiently select events that contain relevant information…

Hardware Architecture · Computer Science 2022-12-09 Natalia Cherezova , Dmitri Mihhailov , Sergei Devadze , Artur Jutman

Maximally recoverable codes are a class of codes which recover from all potentially recoverable erasure patterns given the locality constraints of the code. In earlier works, these codes have been studied in the context of codes with…

Information Theory · Computer Science 2019-04-09 Aaditya M Nair , V. Lalitha

Many combinatorial optimization problems can be approximated within $(1 \pm \epsilon)$ factors in $\text{poly}(\log n, 1/\epsilon)$ rounds in the LOCAL model via network decompositions [Ghaffari, Kuhn, and Maus, STOC 2018]. These approaches…

Data Structures and Algorithms · Computer Science 2025-10-24 Yi-Jun Chang , Hsin-Hao Su

Linear Programming (LP) is an important decoding technique for binary linear codes. However, the advantages of LP decoding, such as low error floor and strong theoretical guarantee, etc., come at the cost of high computational complexity…

Signal Processing · Electrical Eng. & Systems 2020-06-16 Yi Wei , Ming-Min Zhao , Min-Jian Zhao , Ming Lei

This paper investigates data compression that simultaneously allows local decoding and local update. The main result is a universal compression scheme for memoryless sources with the following features. The rate can be made arbitrarily…

Information Theory · Computer Science 2019-10-15 Shashank Vatedka , Aslan Tchamkerten

In this paper, we introduce a novel explicit family of subcodes of Reed-Solomon (RS) codes that efficiently achieve list decoding capacity with a constant output list size. Our approach builds upon the idea of large linear subcodes of RS…

Information Theory · Computer Science 2024-01-29 Amit Berman , Yaron Shany , Itzhak Tamo

An efficient decoding algorithm for horizontally u-interleaved LRPC codes is proposed and analyzed. Upper bounds on the decoding failure rate and the computational complexity of the algorithm are derived. It is shown that interleaving…

Information Theory · Computer Science 2019-08-29 Julian Renner , Thomas Jerkovits , Hannes Bartz

A local algorithm is a distributed algorithm that completes after a constant number of synchronous communication rounds. We present local approximation algorithms for the minimum dominating set problem and the maximum matching problem in…

Distributed, Parallel, and Cluster Computing · Computer Science 2010-02-02 Matti Åstrand , Valentin Polishchuk , Joel Rybicki , Jukka Suomela , Jara Uitto

We show that successive cancellation list decoding can be formulated exclusively using log-likelihood ratios. In addition to numerical stability, the log-likelihood ratio based formulation has useful properties which simplify the sorting…

Information Theory · Computer Science 2016-02-15 Alexios Balatsoukas-Stimming , Mani Bastani Parizi , Andreas Burg

Advances in hardware and language model architecture have spurred a revolution in natural language generation. However, autoregressive models compute probability distributions over next-token choices, and sampling from these distributions,…

Computation and Language · Computer Science 2025-09-10 Tom Kempton , Stuart Burrell

The Learning Parity with Noise (LPN) problem underlines several classic cryptographic primitives. Researchers have attempted to demonstrate the algorithmic hardness of this problem by finding reductions from the decoding problem of linear…

Information Theory · Computer Science 2025-03-19 Madhura Pathegama , Alexander Barg

We focus on erasure codes for distributed storage. The distributed storage setting imposes locality requirements because of easy repair demands on the decoder. We first establish the characterization of various locality properties in terms…

Information Theory · Computer Science 2016-08-30 Margreta Kuijper , Diego Napp

Recent developments have shown the existence of quantum low-density parity check (qLDPC) codes with constant rate and linear distance. A natural question concerns the efficient decodability of these codes. In this paper, we present a linear…

Quantum Physics · Physics 2022-06-15 Shouzhen Gu , Christopher A. Pattison , Eugene Tang

The generation of Register-Transfer Level (RTL) code is a crucial yet labor-intensive step in digital hardware design, traditionally requiring engineers to manually translate complex specifications into thousands of lines of synthesizable…

Machine Learning · Computer Science 2026-02-03 Hanqi Lyu , Di Huang , Yaoyu Zhu , Kangcheng Liu , Bohan Dou , Chongxiao Li , Pengwei Jin , Shuyao Cheng , Rui Zhang , Zidong Du , Qi Guo , Xing Hu , Yunji Chen

In distributed optimization problems, a technique called gradient coding, which involves replicating data points, has been used to mitigate the effect of straggling machines. Recent work has studied approximate gradient coding, which…

Machine Learning · Statistics 2021-08-09 Margalit Glasgow , Mary Wootters

Some new results are derived concerning random coding error exponents and expurgated exponents for list decoding with a deterministic list size $L$. Two asymptotic regimes are considered, the fixed list-size regime, where $L$ is fixed…

Information Theory · Computer Science 2016-11-17 Neri Merhav
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