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This work proves new results on the ability of binary Reed-Muller codes to decode from random errors and erasures. We obtain these results by proving improved bounds on the weight distribution of Reed-Muller codes of high degrees.…

Information Theory · Computer Science 2018-12-03 Ori Sberlo , Amir Shpilka

We prove by construction that the Bravyi-Poulin-Terhal bound on the spatial density of stabilizer codes does not generalize to stabilizer circuits. To do so, we construct a fault tolerant quantum computer with a coding rate above 5% and…

Quantum Physics · Physics 2025-02-25 Craig Gidney , Thiago Bergamaschi

In this paper, we consider the problem of distinguishing the noisy codewords of a known binary linear block code from a random bit sequence. We propose to use the generalized likelihood ratio test (GLRT) to solve this problem. We also give…

Information Theory · Computer Science 2012-11-01 Arti D. Yardi , Saravanan Vijayakumaran

A locally repairable code with availability has the property that every code symbol can be recovered from multiple, disjoint subsets of other symbols of small size. In particular, a code symbol is said to have $(r,t)$-availability if it can…

Information Theory · Computer Science 2017-09-15 Swanand Kadhe , Robert Calderbank

Polarization-adjusted convolutional (PAC) codes were recently proposed and arouse the interest of the channel coding community because they were shown to approach theoretical bounds for the (128,64) code size. In this letter, we propose…

Information Theory · Computer Science 2020-11-09 Thibaud Tonnellier , Warren J. Gross

A Gray code for a combinatorial class is a method for listing the objects in the class so that successive objects differ in some prespecified, small way, typically expressed as a bounded Hamming distance. In a previous work, the authors of…

Combinatorics · Mathematics 2017-03-20 Ahmad Sabri , Vincent Vajnovszki

Sparse coding (SC) is attracting more and more attention due to its comprehensive theoretical studies and its excellent performance in many signal processing applications. However, most existing sparse coding algorithms are nonconvex and…

Machine Learning · Computer Science 2017-09-12 Xiaodong Feng , Zhiwei Tang , Sen Wu

There has been an increase in the use of resilient control algorithms based on the graph theoretic properties of $r$- and $(r,s)$-robustness. These algorithms guarantee consensus of normally behaving agents in the presence of a bounded…

Multiagent Systems · Computer Science 2019-08-15 James Usevitch , Dimitra Panagou

Line codes make it possible to mitigate interference, to prevent short pulses, and to generate streams of bipolar signals with no direct-current (DC) power content through balancing. They find application in magnetic recording (MR) devices,…

Information Theory · Computer Science 2020-05-26 Ahmed Hareedy , Robert Calderbank

Guessing random additive noise decoding (GRAND) is a universal decoding paradigm that decodes by repeatedly testing error patterns until identifying a codeword, where the ordering of tests is generated by the received channel values. On one…

Information Theory · Computer Science 2025-07-14 Li Wan , Huarui Yin , Wenyi Zhang

By a locally recoverable code (LRC), we will in this paper, mean a linear code in which a given code symbol can be recovered by taking a linear combination of at most $r$ other code symbols with $r << k$. A natural extension is to the local…

Information Theory · Computer Science 2018-12-07 S. B. Balaji , Ganesh R. Kini , P. Vijay Kumar

Guessing Random Additive Noise Decoding (GRAND) is a recently proposed universal decoding algorithm for linear error correcting codes. Since GRAND does not depend on the structure of the code, it can be used for any code encountered in…

Information Theory · Computer Science 2020-07-16 Syed Mohsin Abbas , Thibaud Tonnellier , Furkan Ercan , Warren J. Gross

Currently the most popular method of providing robustness certificates is randomized smoothing where an input is smoothed via some probability distribution. We propose a novel approach to randomized smoothing over multiplicative parameters.…

Machine Learning · Computer Science 2022-08-17 Nikita Muravev , Aleksandr Petiushko

We continue the study of statistical/computational tradeoffs in learning robust classifiers, following the recent work of Bubeck, Lee, Price and Razenshteyn who showed examples of classification tasks where (a) an efficient robust…

Machine Learning · Statistics 2019-06-06 Akshay Degwekar , Preetum Nakkiran , Vinod Vaikuntanathan

We perform a smoothed analysis of the GCC-condition number C(A) of the linear programming feasibility problem \exists x\in\R^{m+1} Ax < 0. Suppose that \bar{A} is any matrix with rows \bar{a_i} of euclidean norm 1 and, independently for all…

Optimization and Control · Mathematics 2012-11-06 Peter Bürgisser , Dennis Amelunxen

Any classifier can be "smoothed out" under Gaussian noise to build a new classifier that is provably robust to $\ell_2$-adversarial perturbations, viz., by averaging its predictions over the noise via randomized smoothing. Under the…

Machine Learning · Computer Science 2022-12-21 Jongheon Jeong , Seojin Kim , Jinwoo Shin

Evaluation metrics that are not robust to dialect variation make it impossible to tell how well systems perform for many groups of users, and can even penalize systems for producing text in lower-resource dialects. However, currently, there…

Computation and Language · Computer Science 2022-11-03 Jiao Sun , Thibault Sellam , Elizabeth Clark , Tu Vu , Timothy Dozat , Dan Garrette , Aditya Siddhant , Jacob Eisenstein , Sebastian Gehrmann

We propose a scheme for detecting and correcting faults in any Clifford circuit. The scheme is based on the observation that the set of all possible outcome bit-strings of a Clifford circuit is a linear code, which we call the outcome code.…

Quantum Physics · Physics 2023-05-29 Nicolas Delfosse , Adam Paetznick

Convergence guarantees of many resilient consensus algorithms are based on the graph theoretic properties of $r$- and $(r,s)$-robustness. These algorithms guarantee consensus of normally behaving agents in the presence of a bounded number…

Systems and Control · Computer Science 2019-06-21 James Usevitch , Dimitra Panagou

One of the most important and challenging problems in coding theory is to construct codes with best possible parameters and properties. The class of quasi-cyclic (QC) codes is known to be fertile to produce such codes. Focusing on QC codes…

Information Theory · Computer Science 2021-08-17 Dev Akre , Nuh Aydin , Matthew J. Harrington , Saurav R. Pandey