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Consider two or more strings $\mathbf{x}^1,\mathbf{x}^2,\ldots,$ that are concatenated to form $\mathbf{x}=\langle \mathbf{x}^1,\mathbf{x}^2,\ldots \rangle$. Suppose that up to $\delta$ deletions occur in each of the concatenated strings.…

Information Theory · Computer Science 2023-04-20 Serge Kas Hanna

Correcting insertions/deletions as well as substitution errors simultaneously plays an important role in DNA-based storage systems as well as in classical communications. This paper deals with the fundamental task of constructing codes that…

Information Theory · Computer Science 2020-05-20 Ilia Smagloy , Lorenz Welter , Antonia Wachter-Zeh , Eitan Yaakobi

In the online channel coding model, a sender wishes to communicate a message to a receiver by transmitting a codeword x =(x_1,...,x_n) in {0,1}^n bit by bit via a channel limited to at most pn corruptions. The channel is online in the sense…

Information Theory · Computer Science 2015-03-17 Ishay Haviv , Michael Langberg

The {\em binary deletion channel} with deletion probability $d$ ($\text{BDC}_d$) is a random channel that deletes each bit of the input message i.i.d with probability $d$. It has been studied extensively as a canonical example of a channel…

Information Theory · Computer Science 2023-05-15 Ittai Rubinstein , Roni Con

We study segmented burst-deletion channels motivated by the observation that synchronization errors commonly occur in a bursty manner in real-world settings. In this channel model, transmitted sequences are implicitly divided into…

Information Theory · Computer Science 2025-07-21 Yajuan Liu , Tolga M. Duman

We investigate adaptive single-trial error/erasure decoding of binary codes whose decoder is able to correct e errors and t erasures if le+t<=d-1. Thereby, d is the minimum Hamming distance of the code and 1<l<=2 is the tradeoff parameter…

Information Theory · Computer Science 2010-05-03 Christian Senger , Vladimir R. Sidorenko , Steffen Schober , Martin Bossert , Victor V. Zyablov

We consider binary input deletion/substitution channels, which model certain types of synchronization errors encountered in practice. Specifically, we focus on the regime of small deletion and substitution probabilities, and by extending an…

Information Theory · Computer Science 2025-07-29 Mohammad Kazemi , Tolga M. Duman

In this work, we study linear error-correcting codes against adversarial insertion-deletion (indel) errors. While most constructions for the indel model are nonlinear, linear codes offer compact representations, efficient encoding, and…

Information Theory · Computer Science 2025-10-01 Roee Gross , Roni Con , Eitan Yaakobi

In recent years we have witnessed an increase on the development of methods for submodular optimization, which have been motivated by the wide applicability of submodular functions in real-world data-science problems. In this paper, we…

Data Structures and Algorithms · Computer Science 2022-09-15 Guangyi Zhang , Nikolaj Tatti , Aristides Gionis

We consider the problem of determining the trade-off between the rate and the block-length of polar codes for a given block error probability when we use the successive cancellation decoder. We take the sum of the Bhattacharyya parameters…

Information Theory · Computer Science 2012-05-15 Ali Goli , S. Hamed Hassani , Rudiger Urbanke

Two-dimensional error-correcting codes, where codewords are represented as $n \times n$ arrays over a $q$-ary alphabet, find important applications in areas such as QR codes, DNA-based storage, and racetrack memories. Among the possible…

Information Theory · Computer Science 2026-02-17 Wenhao Liu , Zhengyi Jiang , Zhongyi Huang , Hanxu Hou

We construct constant-sized ensembles of linear error-correcting codes over any fixed alphabet that can correct a given fraction of adversarial erasures at rates approaching the Singleton bound arbitrarily closely. We provide several…

Information Theory · Computer Science 2025-04-07 Yeyuan Chen , Mahdi Cheraghchi , Nikhil Shagrithaya

This paper considers a binary channel with deletions. We derive two close form upper bound on the capacity of binary deletion channel. The first upper bound is based on computing the capacity of an auxiliary channel and we show how the…

Information Theory · Computer Science 2021-03-23 Hassan Tavakoli

The arbitrarily varying channel (AVC) is a channel model whose state is selected maliciously by an adversary. Fixed-blocklength coding assumes a worst-case bound on the adversary's capabilities, which leads to pessimistic results. This…

Information Theory · Computer Science 2009-10-06 Anand D. Sarwate , Michael Gastpar

We give an explicit construction of length-$n$ binary codes capable of correcting the deletion of two bits that have size $2^n/n^{4+o(1)}$. This matches up to lower order terms the existential result, based on an inefficient greedy choice…

Information Theory · Computer Science 2020-07-22 Venkatesan Guruswami , Johan Håstad

Online learning methods yield sequential regret bounds under minimal assumptions and provide in-expectation risk bounds for statistical learning. However, despite the apparent advantage of online guarantees over their statistical…

Machine Learning · Computer Science 2023-08-16 Dirk van der Hoeven , Nikita Zhivotovskiy , Nicolò Cesa-Bianchi

This paper studies codes that correct bursts of deletions. Namely, a code will be called a $b$-burst-deletion-correcting code if it can correct a deletion of any $b$ consecutive bits. While the lower bound on the redundancy of such codes…

Information Theory · Computer Science 2016-05-16 Clayton Schoeny , Antonia Wachter-Zeh , Ryan Gabrys , Eitan Yaakobi

An error correcting code ($\mathsf{ECC}$) allows a sender to send a message to a receiver such that even if a constant fraction of the communicated bits are corrupted, the receiver can still learn the message correctly. Due to their…

Data Structures and Algorithms · Computer Science 2021-11-09 Meghal Gupta , Yael Tauman Kalai , Rachel Zhang

We consider the problem of sequential decision making under uncertainty in which the loss caused by a decision depends on the following binary observation. In competitive on-line learning, the goal is to design decision algorithms that are…

Machine Learning · Computer Science 2007-05-23 Vladimir Vovk

Adversarial training is a principled approach for training robust neural networks. Despite of tremendous successes in practice, its theoretical properties still remain largely unexplored. In this paper, we provide new theoretical insights…

Machine Learning · Computer Science 2019-07-29 Yan Li , Ethan X. Fang , Huan Xu , Tuo Zhao