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Related papers: Threshold rates for properties of random codes

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In this paper, we introduce an achievability bound on the frame error rate of random tree code ensembles under a sequential decoding algorithm with a hard computational limit and consider the optimization of the random tree code ensembles…

Information Theory · Computer Science 2025-01-23 B. Tan Bacinoglu

We prove the following results concerning the list decoding of error-correcting codes: (i) We show that for \textit{any} code with a relative distance of $\delta$ (over a large enough alphabet), the following result holds for \textit{random…

Information Theory · Computer Science 2010-01-13 Atri Rudra , Steve Uurtamo

We provide (high probability) bounds on the condition number of random feature matrices. In particular, we show that if the complexity ratio $\frac{N}{m}$ where $N$ is the number of neurons and $m$ is the number of data samples scales like…

Machine Learning · Statistics 2021-11-08 Zhijun Chen , Hayden Schaeffer

We present a unified framework to study threshold functions for the existence of solutions to linear systems of equations in random sets which includes arithmetic progressions, sum-free sets, $B_{h}[g]$-sets and Hilbert cubes. In…

Combinatorics · Mathematics 2019-02-05 Juanjo Rué , Christoph Spiegel , Ana Zumalacárregui

This paper studies the concentration properties of random codes. Specifically, we show that, for discrete memoryless channels, the error exponent of a randomly generated code with pairwise-independent codewords converges in probability to…

Information Theory · Computer Science 2022-03-16 Lan V. Truong , Giuseppe Cocco , Josep Font-Segura , Albert Guillén i Fàbregas

We determine the exact freezing threshold, r^f, for a family of models of random boolean constraint satisfaction problems, including NAE-SAT and hypergraph 2-colouring, when the constraint size is sufficiently large. If the…

Discrete Mathematics · Computer Science 2012-09-24 Michael Molloy , Ricardo Restrepo

This paper studies random-coding error exponents of randomised list decoding, in which the decoder randomly selects $L$ messages with probabilities proportional to the decoding metric of the codewords. The exponents (or bounds) are given…

Information Theory · Computer Science 2026-01-15 Henrique K. Miyamoto , Sheng Yang

We show that a random puncturing of a code with good distance is list recoverable beyond the Johnson bound. In particular, this implies that there are Reed-Solomon codes that are list recoverable beyond the Johnson bound. It was previously…

Combinatorics · Mathematics 2020-07-07 Ben Lund , Aditya Potukuchi

An NP-hard combinatorial optimization problem $\Pi$ is said to have an {\em approximation threshold} if there is some $t$ such that the optimal value of $\Pi$ can be approximated in polynomial time within a ratio of $t$, and it is NP-hard…

Computational Complexity · Computer Science 2008-12-15 Uriel Feige

Random probabilities are a key component to many nonparametric methods in Statistics and Machine Learning. To quantify comparisons between different laws of random probabilities several works are starting to use the elegant Wasserstein over…

Statistics Theory · Mathematics 2024-05-27 Marta Catalano , Hugo Lavenant

Effective and reliable data retrieval is critical for the feasibility of DNA storage, and the development of random access efficiency plays a key role in its practicality and reliability. In this paper, we study the Random Access Problem,…

Information Theory · Computer Science 2025-10-10 Anina Gruica , Maria Montanucci , Ferdinando Zullo

A metric probability space $M$ admits thresholds if the random geometric graph on $M$ has a threshold for every monotone graph property. We connect the existence of thresholds to the uniform expansion of $M$ and prove that all standard…

Combinatorics · Mathematics 2026-05-21 Bhargav Narayanan

In this work we present a class of locally recoverable codes, i.e. codes where an erasure at a position $P$ of a codeword may be recovered from the knowledge of the entries in the positions of a recovery set $R_P$. The codes in the class…

Information Theory · Computer Science 2021-07-29 Cícero Carvalho , Victor G. L. Neumann

We provide a general framework to study stochastic sequences related to individual learning in economics, learning automata in computer sciences, social learning in marketing, and other applications. More precisely, we study the asymptotic…

Probability · Mathematics 2014-10-07 Carlos Oyarzun , Johannes Ruf

We introduce the notion of a reproducible algorithm in the context of learning. A reproducible learning algorithm is resilient to variations in its samples -- with high probability, it returns the exact same output when run on two samples…

Machine Learning · Computer Science 2023-04-17 Russell Impagliazzo , Rex Lei , Toniann Pitassi , Jessica Sorrell

This paper shows that, with high probability, randomly punctured Reed-Solomon codes over fields of polynomial size achieve the list decoding capacity. More specifically, we prove that for any $\epsilon>0$ and $R\in (0,1)$, with high…

Information Theory · Computer Science 2025-09-03 Zeyu Guo , Zihan Zhang

A locally recoverable code (LRC code) is a code over a finite alphabet such that every symbol in the encoding is a function of a small number of other symbols that form a recovering set. In this paper we derive new finite-length and…

Information Theory · Computer Science 2016-03-10 Itzhak Tamo , Alexander Barg , Alexey Frolov

We present the expected values from p-value hacking as a choice of the minimum p-value among $m$ independents tests, which can be considerably lower than the "true" p-value, even with a single trial, owing to the extreme skewness of the…

Applications · Statistics 2018-01-29 Nassim Nicholas Taleb

We prove several results on linear codes achieving list-recovery capacity. We show that random linear codes achieve list-recovery capacity with constant output list size (independent of the alphabet size and length). That is, over alphabets…

Information Theory · Computer Science 2025-03-03 Ray Li , Nikhil Shagrithaya

Hypergraphs are structures that can be decomposed or described; in other words they are recursively countable. Here, we get exact and asymptotic enumeration results on hypergraphs by means of exponential generating functions. The number of…

Discrete Mathematics · Computer Science 2008-06-20 Tsiriniaina Andriamampianina