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Related papers: List Recovery for Random Low-Rate Linear Codes

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Many real world datasets subsume a linear or non-linear low-rank structure in a very low-dimensional space. Unfortunately, one often has very little or no information about the geometry of the space, resulting in a highly under-determined…

Computer Vision and Pattern Recognition · Computer Science 2016-05-27 Nauman Shahid , Nathanael Perraudin , Pierre Vandergheynst

Motivated by applications such as discovering strong ties in social networks and assembling genome subsequences in biology, we study the problem of recovering a hidden $2k$-nearest neighbor (NN) graph in an $n$-vertex complete graph, whose…

Data Structures and Algorithms · Computer Science 2019-11-21 Jian Ding , Yihong Wu , Jiaming Xu , Dana Yang

We wish to generate list-decodable codes over small alphabets using as little randomness as possible. Specifically, we hope to generate codes achieving what we term the Elias bound, which means that they are $(\rho,L)$-list-decodable with…

Information Theory · Computer Science 2024-05-16 Jonathan Mosheiff , Nicolas Resch , Kuo Shang , Chen Yuan

Maximally recoverable codes are codes designed for distributed storage which combine quick recovery from single node failure and optimal recovery from catastrophic failure. Gopalan et al [SODA 2017] studied the alphabet size needed for such…

Combinatorics · Mathematics 2017-04-04 Daniel Kane , Shachar Lovett , Sankeerth Rao

For a connected weighted hypergraph, we give a randomized almost-linear-time solver for the Poisson problem for the cut-based hypergraph Laplacian in the natural input size $P=\sum_{e\in E}|e|$, the sum of hyperedge sizes. For every fixed…

Data Structures and Algorithms · Computer Science 2026-05-01 Yuichi Yoshida

For every p in (0,1/2), we give an explicit construction of binary codes of rate approaching "capacity" 1-H(p) that enable reliable communication in the presence of worst-case additive errors}, caused by a channel oblivious to the codeword…

Information Theory · Computer Science 2010-05-04 Venkatesan Guruswami , Adam Smith

We investigate theoretical guarantees for the false-negative rate (FNR) -- the fraction of true causal edges whose orientation is not recovered, under single-variable random interventions and an $\epsilon$-interventional faithfulness…

Machine Learning · Computer Science 2025-11-05 Mathieu Chevalley , Arash Mehrjou , Patrick Schwab

This paper studies the parameters for which Reed-Muller (RM) codes over $GF(2)$ can correct random erasures and random errors with high probability, and in particular when can they achieve capacity for these two classical channels.…

Information Theory · Computer Science 2014-11-18 Emmanuel Abbe , Amir Shpilka , Avi Wigderson

We study coded distributed matrix multiplication from an approximate recovery viewpoint. We consider a system of $P$ computation nodes where each node stores $1/m$ of each multiplicand via linear encoding. Our main result shows that the…

Information Theory · Computer Science 2021-05-06 Haewon Jeong , Ateet Devulapalli , Viveck R. Cadambe , Flavio Calmon

A linear-programming decoder for \emph{nonbinary} expander codes is presented. It is shown that the proposed decoder has the maximum-likelihood certificate properties. It is also shown that this decoder corrects any pattern of errors of a…

Information Theory · Computer Science 2016-11-17 Vitaly Skachek

This paper considers the model problem of reconstructing an object from incomplete frequency samples. Consider a discrete-time signal $f \in \C^N$ and a randomly chosen set of frequencies $\Omega$ of mean size $\tau N$. Is it possible to…

Numerical Analysis · Mathematics 2007-05-23 Emmanuel Candes , Justin Romberg , Terence Tao

We consider the problem of recovering elements of a low-dimensional model from linear measurements. From signal and image processing to inverse problems in data science, this question has been at the center of many applications. Lately,…

Signal Processing · Electrical Eng. & Systems 2025-05-15 Yann Traonmilin , Jean François Aujol , Antoine Guennec

Motivated by applications to DNA storage, we study reconstruction and list-reconstruction schemes for integer vectors that suffer from limited-magnitude errors. We characterize the asymptotic size of the intersection of error balls in…

Information Theory · Computer Science 2021-08-24 Hengjia Wei , Moshe Schwartz

We study the largest possible length $B$ of $(B-1)$-dimensional linear codes over $\mathbb{F}_q$ which can correct up to $t$ errors taken from a restricted set $\mathcal{A}\subseteq \mathbb{F}_q^*$. Such codes can be applied to multilevel…

Information Theory · Computer Science 2018-11-09 Igor E. Shparlinski , Arne Winterhof

We consider the problem of estimation of a low-rank matrix from a limited number of noisy rank-one projections. In particular, we propose two fast, non-convex \emph{proper} algorithms for matrix recovery and support them with rigorous…

Machine Learning · Statistics 2017-05-23 Mohammadreza Soltani , Chinmay Hegde

Tensor completion recovers a multi-dimensional array from a limited number of measurements. Using the recently proposed tensor ring (TR) decomposition, in this paper we show that a d-order tensor of dimensional size n and TR rank r can be…

Machine Learning · Computer Science 2020-03-17 Huyan Huang , Yipeng Liu , Ce Zhu

We consider the problem of recovering a lowrank matrix M from a small number of random linear measurements. A popular and useful example of this problem is matrix completion, in which the measurements reveal the values of a subset of the…

Information Theory · Computer Science 2009-10-05 Emmanuel J. Candes , Yaniv Plan

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

The relation between the girth and the guaranteed error correction capability of $\gamma$-left regular LDPC codes when decoded using the bit flipping (serial and parallel) algorithms is investigated. A lower bound on the size of variable…

Information Theory · Computer Science 2016-11-17 Shashi Kiran Chilappagari , Dung Viet Nguyen , Bane Vasic , Michael W. Marcellin

We show that locally repairable codes (LRCs) can be list decoded efficiently beyond the Johnson radius for a large range of parameters by utilizing the local error correction capabilities. The new decoding radius is derived and the…

Information Theory · Computer Science 2018-05-09 Lukas Holzbaur , Antonia Wachter-Zeh
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