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The group testing problem consists of determining a small set of defective items from a larger set of items based on a number of possibly-noisy tests, and is relevant in applications such as medical testing, communication protocols, pattern…

Information Theory · Computer Science 2023-09-19 Jonathan Scarlett , Oliver Johnson

We study the problem of semi-supervised question answering----utilizing unlabeled text to boost the performance of question answering models. We propose a novel training framework, the Generative Domain-Adaptive Nets. In this framework, we…

Computation and Language · Computer Science 2017-04-25 Zhilin Yang , Junjie Hu , Ruslan Salakhutdinov , William W. Cohen

Let $X$ be a set of items of size $n$ , which may contain some defective items denoted by $I$, where $I \subseteq X$. In group testing, a {\it test} refers to a subset of items $Q \subset X$. The test outcome is $1$ (positive) if $Q$…

Data Structures and Algorithms · Computer Science 2023-09-19 Nader H. Bshouty , Gergely Harcos

We consider Bayesian multiple statistical classification problem in the case where the unknown source distributions are estimated from the labeled training sequences, then the estimates are used as nominal distributions in a robust…

Information Theory · Computer Science 2021-10-11 Hüseyin Afşer

Predicting how genetic variation affects phenotypic outcomes at the organismal, cellular, and molecular levels requires deciphering the cis-regulatory code, the sequence rules by which non-coding regions regulate genes. In this perspective,…

In the last 60 years coding theory has been studied a lot over finite fields $\mathbb{F}_q$ or commutative rings $\mathcal{R}$ with unity. Although in $1993$, a study on the classification of the rings (not necessarily commutative or ring…

Information Theory · Computer Science 2022-08-19 Sourav Deb , Isha Kikani , Manish K Gupta

This paper investigates the construction and analysis of permutation codes under the Chebyshev distance. Direct product group permutation (DPGP) codes, independently introduced by Kl\o ve et al. and Tamo et al., represent the best-known…

Information Theory · Computer Science 2025-09-11 Tomoya Hirobe , Kenta Kasai

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

Supervised topic models can help clinical researchers find interpretable cooccurence patterns in count data that are relevant for diagnostics. However, standard formulations of supervised Latent Dirichlet Allocation have two problems.…

Machine Learning · Statistics 2016-12-07 Michael C. Hughes , Huseyin Melih Elibol , Thomas McCoy , Roy Perlis , Finale Doshi-Velez

In a group testing scheme, a set of tests is designed to identify a small number $t$ of defective items that are present among a large number $N$ of items. Each test takes as input a group of items and produces a binary output indicating…

Information Theory · Computer Science 2016-11-17 Arya Mazumdar

Semiquantitative group testing (SQGT) is a pooling method in which the test outcomes represent bounded intervals for the number of defectives. Alternatively, it may be viewed as an adder channel with quantized outputs. SQGT represents a…

Information Theory · Computer Science 2021-02-10 Mahdi Cheraghchi , Ryan Gabrys , Olgica Milenkovic

We study the error threshold of color codes, a class of topological quantum codes that allow a direct implementation of quantum Clifford gates suitable for entanglement distillation, teleportation and fault-tolerant quantum computation. We…

Disordered Systems and Neural Networks · Physics 2009-08-24 Helmut G. Katzgraber , H. Bombin , M. A. Martin-Delgado

In the problem of classical group testing one aims to identify a small subset (of size $d$) diseased individuals/defective items in a large population (of size $n$). This process is based on a minimal number of suitably-designed group tests…

Information Theory · Computer Science 2022-09-26 Xiwei Cheng , Sidharth Jaggi , Qiaoqiao Zhou

In this work, we present a novel upper bound of target error to address the problem for unsupervised domain adaptation. Recent studies reveal that a deep neural network can learn transferable features which generalize well to novel tasks.…

Machine Learning · Computer Science 2019-10-07 Dexuan Zhang , Tatsuya Harada

Predictive coding has emerged as an influential normative model of neural computation, with numerous extensions and applications. As such, much effort has been put into mapping PC faithfully onto the cortex, but there are issues that remain…

Neurons and Cognition · Quantitative Biology 2023-03-07 Siavash Golkar , Tiberiu Tesileanu , Yanis Bahroun , Anirvan M. Sengupta , Dmitri B. Chklovskii

In this paper we study error-correcting codes for the storage of data in synthetic deoxyribonucleic acid (DNA). We investigate a storage model where a data set is represented by an unordered set of $M$ sequences, each of length $L$. Errors…

Information Theory · Computer Science 2020-02-13 Andreas Lenz , Paul H. Siegel , Antonia Wachter-Zeh , Eitan Yaakobi

We study the question of testing structured properties (classes) of discrete distributions. Specifically, given sample access to an arbitrary distribution $D$ over $[n]$ and a property $\mathcal{P}$, the goal is to distinguish between…

Data Structures and Algorithms · Computer Science 2016-01-22 Clément L. Canonne , Ilias Diakonikolas , Themis Gouleakis , Ronitt Rubinfeld

Rank-metric codes, defined as sets of matrices over a finite field with the rank distance, have gained significant attention due to their applications in network coding and connections to diverse mathematical areas. Initially studied by…

Information Theory · Computer Science 2026-01-23 Alessandro Neri , Ferdinando Zullo

Insdel errors occur in communication systems caused by the loss of positional information of the message. Since the work by Guruswami and Wang, there have been some further investigations on the list decoding of insertion codes, deletion…

Information Theory · Computer Science 2020-09-30 Shu Liu , Ivan Tjuawinata , Chaoping Xing

Over the last 30 years, extensive work has been devoted to developing central limit theory for partial sums of subordinated long memory linear time series. A much less studied problem, motivated by questions that are ubiquitous in extreme…

Probability · Mathematics 2026-03-24 Ioan Scheffel , Marco Oesting , Gilles Stupfler