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Certain simplicial complexes are used to construct a subset $D$ of $\mathbb{F}_{2^n}^m$ and $D$, in turn, defines the linear code $C_{D}$ over $\mathbb{F}_{2^n}$ that consists of $(v\cdot d)_{d\in D}$ for $v\in \mathbb{F}_{2^n}^m$. Here we…

Information Theory · Computer Science 2022-04-19 Vidya Sagar , Ritumoni Sarma

Group-testing refers to the problem of identifying (with high probability) a (small) subset of $D$ defectives from a (large) set of $N$ items via a "small" number of "pooled" tests. For ease of presentation in this work we focus on the…

Information Theory · Computer Science 2013-07-11 Sheng Cai , Mohammad Jahangoshahi , Mayank Bakshi , Sidharth Jaggi

For a random quasi-abelian code of rate $r$, it is shown that the GV-bound is a threshold point: if $r$ is less than the GV-bound at $\delta$, then the probability of the relative distance of the random code being greater than $\delta$ is…

Information Theory · Computer Science 2013-07-08 Yun Fan , Liren Lin

We consider Bernoulli nonadaptive group testing with $k = \Theta(n^\theta)$ defectives, for $\theta \in (0,1)$. The practical definite defectives (DD) detection algorithm is known to be optimal for $\theta \geq 1/2$. We give a new upper…

Information Theory · Computer Science 2017-11-27 Matthew Aldridge

This paper is concerned with computationally efficient learning of homogeneous sparse halfspaces in $\mathbb{R}^d$ under noise. Though recent works have established attribute-efficient learning algorithms under various types of label noise…

Machine Learning · Statistics 2021-03-03 Jie Shen , Chicheng Zhang

This paper presents an optimal construction of $N$-bit-delay almost instantaneous fixed-to-variable-length (AIFV) codes, the general form of binary codes we can make when finite bits of decoding delay are allowed. The presented method…

Information Theory · Computer Science 2025-08-29 Ryosuke Sugiura , Masaaki Nishino , Norihito Yasuda , Yutaka Kamamoto , Takehiro Moriya

In many applications, finding adequate labeled data to train predictive models is a major challenge. In this work, we propose methods to use group-level binary labels as weak supervision to train instance-level binary classification models.…

Machine Learning · Computer Science 2021-08-18 Guruprasad Nayak , Rahul Ghosh , Xiaowei Jia , Vipin Kumar

Score-based generative models (SGMs) aim at estimating a target data distribution by learning score functions using only noise-perturbed samples from the target.Recent literature has focused extensively on assessing the error between the…

Statistics Theory · Mathematics 2025-01-28 Stanislas Strasman , Antonio Ocello , Claire Boyer , Sylvain Le Corff , Vincent Lemaire

Universal variable-to-fixed (V-F) length coding of $d$-dimensional exponential family of distributions is considered. We propose an achievable scheme consisting of a dictionary, used to parse the source output stream, making use of the…

Information Theory · Computer Science 2017-08-02 Nematollah Iri , Oliver Kosut

In this paper, a lemma in algebraic coding theory is established, which is frequently appeared in the encoding and decoding for algebraic codes such as Reed-Solomon codes and algebraic geometry codes. This lemma states that two vector…

Information Theory · Computer Science 2012-08-28 Hajime Matsui

It has been shown that good structured codes over non-Abelian groups do exist. Specifically, we construct codes over the smallest non-Abelian group $\mathds{D}_6$ and show that the performance of these codes is superior to the performance…

Information Theory · Computer Science 2012-02-22 Aria G. Sahebi , S. Sandeep Pradhan

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

Stochastic Gradient Langevin Dynamics (SGLD) is a sampling scheme for Bayesian modeling adapted to large datasets and models. SGLD relies on the injection of Gaussian Noise at each step of a Stochastic Gradient Descent (SGD) update. In this…

Machine Learning · Computer Science 2018-06-11 Henri Palacci , Henry Hess

We give the first efficient algorithm for learning halfspaces in the testable learning model recently defined by Rubinfeld and Vasilyan (2023). In this model, a learner certifies that the accuracy of its output hypothesis is near optimal…

Machine Learning · Computer Science 2023-03-14 Aravind Gollakota , Adam R. Klivans , Konstantinos Stavropoulos , Arsen Vasilyan

In this work, we present the first local-decoding algorithm for expander codes. This yields a new family of constant-rate codes that can recover from a constant fraction of errors in the codeword symbols, and where any symbol of the…

Information Theory · Computer Science 2015-01-08 Brett Hemenway , Rafail Ostrovsky , Mary Wootters

We consider the problem of describing the typical (possibly) non-linear code of minimum distance bounded from below over a large alphabet. We concentrate on block codes with the Hamming metric and on subspace codes with the injection…

Information Theory · Computer Science 2021-11-24 Anina Gruica , Alberto Ravagnani

Sequential testing problems involve a complex system with several components, each of which is "working" with some independent probability. The outcome of each component can be determined by performing a test, which incurs some cost. The…

Data Structures and Algorithms · Computer Science 2023-08-22 Rohan Ghuge , Anupam Gupta , Viswanath Nagarajan

A family of distance-optimal LRC codes from certain subcodes of $q$-ary Reed-Solomon codes, proposed by I.~Tamo and A.~Barg in 2014, assumes that the code length $n$ is a multiple of $r+1.$ By shortening codes from this family, we show that…

Information Theory · Computer Science 2018-02-02 Oleg Kolosov , Alexander Barg , Itzhak Tamo , Gala Yadgar

Spatially-coupled (SC) codes are a class of low-density parity-check (LDPC) codes that have excellent performance thanks to the degrees of freedom they offer. An SC code is designed by partitioning a base matrix into components, the number…

Information Theory · Computer Science 2026-05-11 Bade Aksoy , Doğukan Özbayrak , Ahmed Hareedy

This work presents an adaptive group testing framework for the range-based high dimensional near neighbor search problem. Our method efficiently marks each item in a database as neighbor or non-neighbor of a query point, based on a cosine…

Data Structures and Algorithms · Computer Science 2024-09-10 Harsh Shah , Kashish Mittal , Ajit Rajwade