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Related papers: Cascading Parity-Check Error-Correcting Codes

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We show in this work that reinforcement learning can be successfully applied to decoding short to moderate length sparse graph-based channel codes. Specifically, we focus on low-density parity check (LDPC) codes, which for example have been…

Information Theory · Computer Science 2020-10-20 Salman Habib , Allison Beemer , Joerg Kliewer

The use of parity-check gates in information theory has proved to be very efficient. In particular, error correcting codes based on parity checks over low-density graphs show excellent performances. Another basic issue of information…

Disordered Systems and Neural Networks · Physics 2007-05-23 S. Ciliberti , M. Mezard , R. Zecchina

It is shown that some well-known and some new cyclic codes with orthogonal parity-check equations can be constructed in the finite-field transform domain. It is also shown that, for some binary linear cyclic codes, the performance of the…

Information Theory · Computer Science 2007-07-13 C. Tjhai , M. Tomlinson , R. Horan , M. Ambroze , M. Ahmed

Quantitative properties of stochastic systems are usually specified in logics that allow one to compare the measure of executions satisfying certain temporal properties with thresholds. The model checking problem for stochastic systems with…

Logic in Computer Science · Computer Science 2010-05-11 Axel Legay , Benoit Delahaye

We study efficient algorithms for Sparse PCA in standard statistical models (spiked covariance in its Wishart form). Our goal is to achieve optimal recovery guarantees while being resilient to small perturbations. Despite a long history of…

Machine Learning · Computer Science 2020-11-13 Tommaso d'Orsi , Pravesh K. Kothari , Gleb Novikov , David Steurer

A polynomial matrix inequality is a formula asserting that a polynomial matrix is positive semidefinite. Polynomial matrix optimization concerns minimizing the smallest eigenvalue of a symmetric polynomial matrix subject to a tuple of…

Optimization and Control · Mathematics 2025-06-06 Jared Miller , Jie Wang , Feng Guo

Matrix multiplication is a fundamental building block for large scale computations arising in various applications, including machine learning. There has been significant recent interest in using coding to speed up distributed matrix…

Information Theory · Computer Science 2019-05-17 Wei-Ting Chang , Ravi Tandon

We consider spatially coupled low-density parity-check codes with finite smoothing parameters. A finite smoothing parameter is important for designing practical codes that are decoded using low-complexity windowed decoders. By optimizing…

Information Theory · Computer Science 2017-01-27 Laurent Schmalen , Vahid Aref , Fanny Jardel

A product code with single parity-check component codes can be described via the tools of a multi-kernel polar code, where the rows of the generator matrix are chosen according to the constraints imposed by the product code construction.…

Information Theory · Computer Science 2021-07-27 Mustafa Cemil Coşkun , Gianluigi Liva , Alexandre Graell i Amat , Michael Lentmaier , Henry D. Pfister

Chase-like decoding algorithms are a popular choice for soft-input decoding of algebraic codes. In this paper, we evaluate the performance of different test pattern sets using three methods. For test pattern sets with a certain structure…

Information Theory · Computer Science 2026-05-12 Tim Janz , Simon Obermüller , Andreas Zunker , Stephan ten Brink

This paper investigates fairness and bias in Canonical Correlation Analysis (CCA), a widely used statistical technique for examining the relationship between two sets of variables. We present a framework that alleviates unfairness by…

Machine Learning · Computer Science 2023-09-28 Zhuoping Zhou , Davoud Ataee Tarzanagh , Bojian Hou , Boning Tong , Jia Xu , Yanbo Feng , Qi Long , Li Shen

In this paper, we study polar codes from a practical point of view. In particular, we study concatenated polar codes and rate-compatible polar codes. First, we propose a concatenation scheme including polar codes and Low-Density…

Information Theory · Computer Science 2011-07-28 Ali Eslami , Hossein Pishro-Nik

In this paper, we propose a new erasure decoding algorithm for convolutional codes using the generator matrix. This implies that our decoding method also applies to catastrophic convolutional codes in opposite to the classic approach using…

Information Theory · Computer Science 2025-04-23 Julia Lieb , Raquel Pinto , Carlos Vela

Sparse modeling is a powerful framework for data analysis and processing. Traditionally, encoding in this framework is done by solving an l_1-regularized linear regression problem, usually called Lasso. In this work we first combine the…

Information Theory · Computer Science 2010-03-02 Pablo Sprechmann , Ignacio Ramirez , Guillermo Sapiro , Yonina C. Eldar

In this paper, we present an optimal metric function on average, which leads to a significantly low decoding computation while maintaining the superiority of the polarization-adjusted convolutional (PAC) codes' error-correction performance.…

Information Theory · Computer Science 2020-12-11 Mohsen Moradi

Deep stereo matching has made significant progress in recent years. However, state-of-the-art methods are based on expensive 4D cost volume, which limits their use in real-world applications. To address this issue, 3D correlation maps and…

Computer Vision and Pattern Recognition · Computer Science 2022-01-03 Xiaoming Zhao , Weihai Chen , Xingming Wu , Peter C. Y. Chen , Zhengguo Li

In this paper, we propose a new design method of irregular spatially-coupled low-density parity-check (SC-LDPC) codes with non-uniform degree distributions by linear programming (LP). In general, irregular SC-LDPC codes with non-uniform…

Information Theory · Computer Science 2018-03-28 Heeyoul Kwak , Jong-Seon No , Hosung Park

This paper investigates universal polar coding schemes. In particular, a notion of ordering (called convolutional path) is introduced between probability distributions to determine when a polar compression (or communication) scheme designed…

Information Theory · Computer Science 2010-12-03 Emmanuel Abbe

Sparse coding has achieved a great success in various image processing tasks. However, a benchmark to measure the sparsity of image patch/group is missing since sparse coding is essentially an NP-hard problem. This work attempts to fill the…

Computer Vision and Pattern Recognition · Computer Science 2020-02-06 Zhiyuan Zha , Xin Yuan , Bihan Wen , Jiantao Zhou , Jiachao Zhang , Ce Zhu

We introduce a new method for decoding short and moderate length linear block codes with dense parity-check matrix representations of cyclic form, termed multiple-bases belief-propagation (MBBP). The proposed iterative scheme makes use of…

Information Theory · Computer Science 2016-11-15 Thorsten Hehn , Johannes B. Huber , Olgica Milenkovic , Stefan Laendner