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This work continues the study of linear error correcting codes against adversarial insertion deletion errors (insdel errors). Previously, the work of Cheng, Guruswami, Haeupler, and Li \cite{CGHL21} showed the existence of asymptotically…

Information Theory · Computer Science 2023-03-31 Kuan Cheng , Zhengzhong Jin , Xin Li , Zhide Wei , Yu Zheng

Motivated by applications in DNA-based storage, we study explicit encoding and decoding schemes of binary strings satisfying locally balanced constraints, where the $(\ell,\delta)$-locally balanced constraint requires that the weight of any…

Information Theory · Computer Science 2022-01-31 Chen Wang , Ziyang Lu , Zhaojun Lan , Gennian Ge , Yiwei Zhang

In this paper, we consider a broadcasting process in which information is propagated from a given root node on a noisy tree network, and answer the question that whether the symbols at the nth level of the tree contain non-vanishing…

Probability · Mathematics 2019-02-20 Wenjian Liu , Ning Ning

Motivated by communication channels in which the transmitted sequences are subject to random permutations, as well as by certain DNA storage systems, we study the error control problem in settings where the information is stored/transmitted…

Information Theory · Computer Science 2020-08-13 Mladen Kovačević , Vincent Y. F. Tan

We investigate the length $\ell(n,k)$ of a shortest preset distinguishing sequence (PDS) in the worst case for a $k$-element subset of an $n$-state Mealy automaton. It was mentioned by Sokolovskii that this problem is closely related to the…

Formal Languages and Automata Theory · Computer Science 2014-12-02 Pavel Panteleev

We propose a novel optimization scheme designed to find optimally correctable subspace codes for a known quantum noise channel. To each candidate subspace code we first associate a universal recovery map, as if the code was perfectly…

Quantum Physics · Physics 2024-10-29 Miguel Casanova , Kentaro Ohki , Francesco Ticozzi

Burst errors involving simultaneous insertions, deletions, and substitutions occur in practical scenarios, including DNA data storage and document synchronization, motivating developments of channel codes that can correct such errors. In…

Information Theory · Computer Science 2026-01-23 Yajuan Liu , Tolga M. Duman

Convolutional neural networks (CNNs) have developed to become powerful models for various computer vision tasks ranging from object detection to semantic segmentation. However, most of the state-of-the-art CNNs cannot be deployed directly…

Computer Vision and Pattern Recognition · Computer Science 2021-08-20 Kevin Bui , Fredrick Park , Shuai Zhang , Yingyong Qi , Jack Xin

We prove that for any integer $k\geq 2$ and $\varepsilon>0$, there is an integer $\ell_0\geq 1$ such that any $k$-uniform hypergraph on $n$ vertices with minimum codegree at least $(1/2+\varepsilon)n$ has a fractional decomposition into…

Combinatorics · Mathematics 2021-01-15 Felix Joos , Marcus Kühn

This paper considers the model problem of reconstructing an object from incomplete frequency samples. Consider a discrete-time signal $f \in \C^N$ and a randomly chosen set of frequencies $\Omega$ of mean size $\tau N$. Is it possible to…

Numerical Analysis · Mathematics 2007-05-23 Emmanuel Candes , Justin Romberg , Terence Tao

Reed-Muller codes are some of the oldest and most widely studied error-correcting codes, of interest for both their algebraic structure as well as their many algorithmic properties. A recent beautiful result of Saptharishi, Shpilka and Volk…

Information Theory · Computer Science 2017-12-19 Swastik Kopparty , Aditya Potukuchi

We study the reconstruction problem of permutation sequences from their $k$-minors, which are subsequences of length $k$ with entries renumbered by $1,2,\ldots,k$ preserving order. We prove that the minimum number $k$ such that any…

Combinatorics · Mathematics 2024-11-20 Yiming Ma , Wenjie Zhong , Xiande Zhang

The problem of reconstructing a sequence from the set of its length-$k$ substrings has received considerable attention due to its various applications in genomics. We study an uncoded version of this problem where multiple random sources…

Information Theory · Computer Science 2023-05-11 Kel Levick , Ilan Shomorony

In this work, we revisit the problem of semi-supervised named entity recognition (NER) focusing on extremely light supervision, consisting of a lexicon containing only 10 examples per class. We introduce ELLEN, a simple, fully modular,…

Computation and Language · Computer Science 2025-02-26 Haris Riaz , Razvan-Gabriel Dumitru , Mihai Surdeanu

In the trace reconstruction problem, one attempts to reconstruct a fixed but unknown string $x$ of length $n$ from a given number of traces $\tilde{x}$ drawn iid from the application of a noisy process (such as the deletion channel) to $x$.…

Data Structures and Algorithms · Computer Science 2024-10-17 Ittai Rubinstein

We consider the redundancy of the exact channel synthesis problem under an i.i.d. assumption. Existing results provide an upper bound on the unnormalized redundancy that is logarithmic in the block length. We show, via an improved scheme,…

Information Theory · Computer Science 2024-01-31 Sharang M. Sriramu , Aaron B. Wagner

We consider the problem of joint source and channel coding of structured data such as natural language over a noisy channel. The typical approach to this problem in both theory and practice involves performing source coding to first…

Information Theory · Computer Science 2018-02-21 Nariman Farsad , Milind Rao , Andrea Goldsmith

This work gives an explicit construction of a family of error correcting codes for the binary deletion channel and for the Poisson repeat channel. In the binary deletion channel with parameter $p$ (BDC$_p$) every bit is deleted…

Information Theory · Computer Science 2019-10-16 Roni Con , Amir Shpilka

A general method of coding over expansions is proposed, which allows one to reduce the highly non-trivial problem of coding over continuous channels to a much simpler discrete ones. More specifically, the focus is on the additive…

Information Theory · Computer Science 2012-02-09 O. Ozan Koyluoglu , Kumar Appaiah , Hongbo Si , Sriram Vishwanath

Recent advances in training deep (multi-layer) architectures have inspired a renaissance in neural network use. For example, deep convolutional networks are becoming the default option for difficult tasks on large datasets, such as image…

Neural and Evolutionary Computing · Computer Science 2016-02-17 Mark D. McDonnell , Migel D. Tissera , Tony Vladusich , André van Schaik , Jonathan Tapson
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