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In the search for highly efficient decoders for short LDPC codes approaching maximum likelihood performance, a relayed decoding strategy, specifically activating the ordered statistics decoding process upon failure of a neural min-sum…

Information Theory · Computer Science 2024-03-26 Guangwen Li , Xiao Yu

In this paper we consider lossless source coding for a class of sources specified by the total variational distance ball centred at a fixed nominal probability distribution. The objective is to find a minimax average length source code,…

Information Theory · Computer Science 2013-01-25 Themistoklis Charalambous , Charalambos D. Charalambous , Sergey Loyka

LLMs show strong performance in code generation, but their outputs lack correctness guarantees. Sample-based uncertainty estimators address this by generating multiple candidate programs and measuring their disagreement. However, existing…

Software Engineering · Computer Science 2026-05-12 Weilin He , Arindam Sharma , Cristina David

Despite strong performance on a variety of tasks, neural sequence models trained with maximum likelihood have been shown to exhibit issues such as length bias and degenerate repetition. We study the related issue of receiving…

Machine Learning · Computer Science 2020-10-06 Sean Welleck , Ilia Kulikov , Jaedeok Kim , Richard Yuanzhe Pang , Kyunghyun Cho

The design of block codes for short information blocks (e.g., a thousand or less information bits) is an open research problem that is gaining relevance thanks to emerging applications in wireless communication networks. In this paper, we…

Information Theory · Computer Science 2019-03-12 Mustafa Cemil Coşkun , Giuseppe Durisi , Thomas Jerkovits , Gianluigi Liva , William Ryan , Brian Stein , Fabian Steiner

Probability estimation is essential for every statistical data compression algorithm. In practice probability estimation should be adaptive, recent observations should receive a higher weight than older observations. We present a…

Information Theory · Computer Science 2015-01-12 Christopher Mattern

In this paper, we study the tradeoffs between complexity and reliability for decoding large linear block codes. We show that using artificial neural networks to predict the required order of an ordered statistics based decoder helps in…

Information Theory · Computer Science 2021-03-08 Baptiste Cavarec , Hasan Basri Celebi , Mats Bengtsson , Mikael Skoglund

Most calculations performed by the average R user are unremarkable in the sense that nowadays, any computer can crush the related code in a matter of seconds. But more and more often, heavy calculations are also performed using R, something…

Computation · Statistics 2015-03-04 Nathan Uyttendaele

This paper explores feedback systems using incremental redundancy (IR) with noiseless transmitter confirmation (NTC). For IR-NTC systems based on {\em finite-length} codes (with blocklength $N$) and decoding attempts only at {\em certain…

Information Theory · Computer Science 2013-09-04 Tsung-Yi Chen , Adam R. Williamson , Nambi Seshadri , Richard D. Wesel

Let C be a linear code with length n and minimum distance d. The stopping redundancy of C is defined as the minimum number of rows in a parity-check matrix for C such that the smallest stopping sets in the corresponding Tanner graph have…

Information Theory · Computer Science 2007-07-13 Junsheng Han , Paul H. Siegel

Many problems related to the quality of requirements arise during elicitation and specification activities since they are written in natural language. The flexibility and inherent nature of language make requirements prone to…

Software Engineering · Computer Science 2021-05-14 María Guadalupe Gramajo , Luciana Ballejos , Mariel Ale

Redundancy for straggler mitigation, originally in data download and more recently in distributed computing context, has been shown to be effective both in theory and practice. Analysis of systems with redundancy has drawn significant…

Performance · Computer Science 2017-10-03 Mehmet Fatih Aktas , Pei Peng , Emina Soljanin

Recurrent neural networks are a powerful tool, but they are very sensitive to their hyper-parameter configuration. Moreover, training properly a recurrent neural network is a tough task, therefore selecting an appropriate configuration is…

Machine Learning · Computer Science 2019-03-12 Andrés Camero , Jamal Toutouh , Enrique Alba

Large Language Models for code often entail significant computational complexity, which grows significantly with the length of the input code sequence. We propose LeanCode for code simplification to reduce training and prediction time,…

Software Engineering · Computer Science 2026-02-06 Yan Wang , Ling Ding , Tien N Nguyen , Shaohua Wang , Yanan Zheng

We consider the problem of constructing a code capable of correcting a single long tandem duplication error of variable length. As the main contribution of this paper, we present a $q$-ary efficiently encodable code of length $n+1$ and…

Information Theory · Computer Science 2023-04-26 Daniil Goshkoder , Nikita Polyanskii , Ilya Vorobyev

A pruned variant of polar coding is reinvented for all binary erasure channels. For small $\varepsilon>0$, we construct codes with block length $\varepsilon^{-5}$, code rate $\text{Capacity}-\varepsilon$, error probability $\varepsilon$,…

Information Theory · Computer Science 2018-12-20 Hsin-Po Wang , Iwan Duursma

This paper considers rateless network error correction codes for reliable multicast in the presence of adversarial errors. Most existing network error correction codes are designed for a given network capacity and maximum number of errors…

Information Theory · Computer Science 2013-01-15 Wentao Huang , Tracey Ho , Hongyi Yao , Sidharth Jaggi

Random linear codes are a workhorse in coding theory, and are used to show the existence of codes with the best known or even near-optimal trade-offs in many noise models. However, they have little structure besides linearity, and are not…

Computational Complexity · Computer Science 2024-07-11 Venkatesan Guruswami , Jonathan Mosheiff

his study presents a novel technique to estimate the computational complexity of sequential decoding using the Berry-Esseen theorem. Unlike the theoretical bounds determined by the conventional central limit theorem argument, which often…

Information Theory · Computer Science 2007-08-20 Po-Ning Chen , Yunghsiang S. Han , Carlos R. P. Hartmann , Hong-Bin Wu

This research paper aims to find, analyze and understand code patterns in any software system and measure its quality by defining standards and proposing a formula for the same. Every code that is written can be divided into different code…

Software Engineering · Computer Science 2011-07-01 Jitesh Dundas
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