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Related papers: Robust Gray Codes Approaching the Optimal Rate

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A robust Gray code, formally introduced by (Lolck and Pagh, SODA 2024), is a Gray code that additionally has the property that, given a noisy version of the encoding of an integer $j$, it is possible to reconstruct $\hat{j}$ so that $|j -…

Information Theory · Computer Science 2024-01-30 Dorsa Fathollahi , Mary Wootters

Modern applications are driving demand for ultra-reliable low-latency communications, rekindling interest in the performance of short, high-rate error correcting codes. To that end, here we introduce a soft-detection variant of Guessing…

Information Theory · Computer Science 2021-06-16 Ken R. Duffy

To ensure differential privacy, one can reveal an integer fuzzily in two ways: (a) add some Laplace noise to the integer, or (b) encode the integer as a binary string and add iid BSC noise. The former is simple and natural while the latter…

Information Theory · Computer Science 2024-06-26 Venkatesan Guruswami , Hsin-Po Wang

Guessing Random Additive Noise Decoding (GRAND) is a family of hard- and soft-detection error correction decoding algorithms that provide accurate decoding of any moderate redundancy code of any length. Here we establish a method through…

Information Theory · Computer Science 2023-08-11 Kevin Galligan , Peihong Yuan , Muriel Médard , Ken R. Duffy

The design and implementation of error correcting codes has long been informed by two fundamental results: Shannon's 1948 capacity theorem, which established that long codes use noisy channels most efficiently; and Berlekamp, McEliece, and…

Information Theory · Computer Science 2024-10-30 Ken R. Duffy , Muriel Médard , Wei An

An encoder wishes to minimize the bit rate necessary to guarantee that a decoder is able to calculate a symbolwise function of a sequence available only at the encoder and a sequence that can be measured only at the decoder. This classical…

Information Theory · Computer Science 2012-04-19 Behzad Ahmadi , Osvaldo Simeone

An encoder wishes to minimize the bit rate necessary to guarantee that a decoder is able to calculate a symbol-wise function of a sequence available only at the encoder and a sequence that can be measured only at the decoder. This classical…

Information Theory · Computer Science 2012-04-17 Behzad Ahmadi , Osvaldo Simeone

A new class of folded subspace codes for noncoherent network coding is presented. The codes can correct insertions and deletions beyond the unique decoding radius for any code rate $R\in[0,1]$. An efficient interpolation-based decoding…

Information Theory · Computer Science 2015-04-22 Hannes Bartz , Vladimir Sidorenko

This work constructs codes that are efficiently decodable from a constant fraction of \emph{worst-case} insertion and deletion errors in three parameter settings: (i) Binary codes with rate approaching 1; (ii) Codes with constant rate for…

Information Theory · Computer Science 2016-05-17 Venkatesan Guruswami , Ray Li

We consider coding schemes for computationally bounded channels, which can introduce an arbitrary set of errors as long as (a) the fraction of errors is bounded with high probability by a parameter $p$ and (b) the process which adds the…

Information Theory · Computer Science 2013-03-01 Venkatesan Guruswami , Adam Smith

Concurrent coding is an encoding scheme with "holographic" type properties that are shown here to be robust against a significant amount of noise and signal loss. This single encoding scheme is able to correct for random errors and burst…

Information Theory · Computer Science 2016-04-27 David M. Benton

A hybrid automatic repeat request (HARQ) scheme based on a novel class of rate-compatible polar (\mbox{RCP}) codes are proposed. The RCP codes are constructed by performing punctures and repetitions on the conventional polar codes.…

Information Theory · Computer Science 2016-11-17 Kai Chen , Kai Niu , Jiaru Lin

We consider a distributed source coding system in which several observations are communicated to the decoder using limited transmission rate. The observations must be separately coded. We introduce a robust distributed coding scheme which…

Information Theory · Computer Science 2007-07-13 Jun Chen , Toby Berger

We study uniquely decodable codes and list decodable codes in the high-noise regime, specifically codes that are uniquely decodable from $\frac{1-\varepsilon}{2}$ fraction of errors and list decodable from $1-\varepsilon$ fraction of…

Information Theory · Computer Science 2024-11-06 Xin Li , Songtao Mao

We introduce a binary embedding framework, called Proximity Preserving Code (PPC), which learns similarity and dissimilarity between data points to create a compact and affinity-preserving binary code. This code can be used to apply fast…

Machine Learning · Computer Science 2020-02-06 Inbal Lav , Shai Avidan , Yoram Singer , Yacov Hel-Or

We initiate the study of what we term ``fast good codes'' with ``fast good duals.'' Specifically, we consider the task of constructing a rate 1/2 binary linear code such that both it and its dual are asymptotically good (in fact, have…

Information Theory · Computer Science 2026-01-12 Martijn Brehm , Nicolas Resch

Guessing Random Additive Noise Decoding (GRAND) is a universal decoding algorithm that has been recently proposed as a practical way to perform maximum likelihood decoding. It generates a sequence of possible error patterns and applies them…

Information Theory · Computer Science 2022-02-09 Carlo Condo

Decoding via sequentially guessing the error pattern in a received noisy sequence has received attention recently, and ORBGRAND has been proposed as one such decoding algorithm that is capable of utilizing the soft information embedded in…

Information Theory · Computer Science 2022-12-20 Mengxiao Liu , Yuejun Wei , Zhenyuan Chen , Wenyi Zhang

In this paper, we consider the problem of robust joint source-channel coding over an additive white Gaussian noise channel. We propose a new scheme which achieves the optimal slope of the signal-to-distortion (SDR) curve (unlike the…

Information Theory · Computer Science 2008-05-28 Mahmoud Taherzadeh , Amir K. Khandani

We study the trade-offs between convergence rate and robustness to gradient errors in designing a first-order algorithm. We focus on gradient descent (GD) and accelerated gradient (AG) methods for minimizing strongly convex functions when…

Optimization and Control · Mathematics 2019-11-07 Necdet Serhat Aybat , Alireza Fallah , Mert Gurbuzbalaban , Asuman Ozdaglar
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