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Deep Neural Networks (DNNs) have been shown to be susceptible to memorization or overfitting in the presence of noisily-labelled data. For the problem of robust learning under such noisy data, several algorithms have been proposed. A…

Machine Learning · Computer Science 2022-12-06 Deep Patel , P. S. Sastry

We consider the problem of constructing an erasure code for storage over a network when the data sources are distributed. Specifically, we assume that there are n storage nodes with limited memory and k<n sources generating the data. We…

Information Theory · Computer Science 2016-11-15 Alexandros G. Dimakis , Vinod Prabhakaran , Kannan Ramchandran

Most soundfield synthesis approaches deal with extensive and regular loudspeaker arrays, which are often not suitable for home audio systems, due to physical space constraints. In this article we propose a technique for soundfield synthesis…

Audio and Speech Processing · Electrical Eng. & Systems 2024-07-09 Luca Comanducci , Fabio Antonacci , Augusto Sarti

We consider the problem of efficiently designing sets (codes) of equal-length DNA strings (words) that satisfy certain combinatorial constraints. This problem has numerous motivations including DNA computing and DNA self-assembly. Previous…

Data Structures and Algorithms · Computer Science 2007-05-23 Ming-Yang Kao , Manan Sanghi , Robert Schweller

Motivation: DNA data is transcribed into single-stranded RNA, which folds into specific molecular structures. In this paper we pose the question to what extent sequence- and structure-information correlate. We view this correlation as…

Combinatorics · Mathematics 2016-08-23 Christopher Barrett , Fenix W. Huang , Christian M. Reidys

In this paper, we examine the problem of information storage on memristors affected by resistive drift noise under energy constraints. We introduce a novel, fundamental trade-off between the information lifetime of memristive states and the…

Emerging Technologies · Computer Science 2025-01-22 Waleed El-Geresy , Christos Papavassiliou , Deniz Gündüz

The sequence reconstruction problem for insertion/deletion channels has attracted significant attention owing to their applications recently in some emerging data storage systems, such as racetrack memories, DNA-based data storage. Our goal…

Information Theory · Computer Science 2026-04-24 Van Long Phuoc Pham , Yeow Meng Chee , Kui Cai , Van Khu Vu

A hypercomplex representation of DNA is proposed to facilitate comparison of DNA sequences with fuzzy composition. Using hypercomplex number representation, conventional sequence analysis method, such as, dot matrix analysis, dynamic…

Quantitative Methods · Quantitative Biology 2023-08-03 Jian-Jun Shu , Yajing Li

With recent advancements in next-generation data storage, especially in biological molecule-based storage, insertion, deletion, and substitution (IDS) error-correcting codes have garnered increased attention. However, a universal method for…

Information Theory · Computer Science 2025-11-11 Alan J. X. Guo , Mengyi Wei , Yufan Dai , Yali Wei , Pengchen Zhang

Noisy label learning aims to train deep neural networks using a large amount of samples with noisy labels, whose main challenge comes from how to deal with the inaccurate supervision caused by wrong labels. Existing works either take the…

Machine Learning · Computer Science 2024-04-03 Sihan Bai

DNA is an attractive candidate for data storage. Its millennial durability and nanometer scale offer exceptional data density and longevity. Its relevance to medical applications also drives advances in DNA-related biotechnology. To protect…

Information Theory · Computer Science 2025-11-25 Yu-Ting Lin , Hsin-Po Wang , Venkatesan Guruswami

The design of codes for feedback-enabled communications has been a long-standing open problem. Recent research on non-linear, deep learning-based coding schemes have demonstrated significant improvements in communication reliability over…

Information Theory · Computer Science 2023-06-09 Junghoon Kim , Taejoon Kim , David Love , Christopher Brinton

This study proposes a deep learning-based approach for discovering loops in programming code according to their potential for parallelization. Two genetic algorithm-based code generators were developed to produce two distinct types of code:…

Machine Learning · Computer Science 2025-10-03 Izavan dos S. Correia , Henrique C. T. Santos , Tiago A. E. Ferreira

This paper considers the comparison of noisy channels from the viewpoint of statistical decision theory. Various orderings are discussed, all formalizing the idea that one channel is "better" than another for information transmission. The…

Information Theory · Computer Science 2018-03-09 Francesco Buscemi

Deep joint source-channel coding (DeepJSCC) has emerged as a powerful paradigm for end-to-end semantic communications, jointly learning to compress and protect task-relevant features over noisy channels. However, existing DeepJSCC schemes…

In the problem of blind reconstruction of channel codes, the receiver does not have the knowledge of the channel code used at the transmitter and the aim is to identify this unknown channel code corresponding to the given received sequence.…

Information Theory · Computer Science 2017-10-13 Arti D. Yardi , Saravanan Vijayakumaran

Coding theory is a central discipline underpinning wireline and wireless modems that are the workhorses of the information age. Progress in coding theory is largely driven by individual human ingenuity with sporadic breakthroughs over the…

Machine Learning · Statistics 2018-05-24 Hyeji Kim , Yihan Jiang , Ranvir Rana , Sreeram Kannan , Sewoong Oh , Pramod Viswanath

Genomic data sets are growing dramatically as the cost of sequencing continues to decline and small sequencing devices become available. Enormous community databases store and share this data with the research community, but some of these…

DNA exhibits remarkable potential as a data storage solution due to its impressive storage density and long-term stability, stemming from its inherent biomolecular structure. However, developing this novel medium comes with its own set of…

Image and Video Processing · Electrical Eng. & Systems 2023-09-14 Trung Hieu Le , Xavier Pic , Jeremy Mateos , Marc Antonini

We study the problem of secure joint source-channel coding for multimodal semantic sources transmitted over noisy wiretap channels. The source model consists of $m$ modalities (e.g., image, audio, and sensor data), all represented as random…

Information Theory · Computer Science 2026-05-26 Denis Kozlov , Mahtab Mirmohseni , Rahim Tafazolli
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