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Assuming that we have a soft-decision list decoding algorithm of a linear code, a new hard-decision list decoding algorithm of its repeated code is proposed in this article. Although repeated codes are not used for encoding data, due to…

Information Theory · Computer Science 2024-05-01 Fernando Hernando , Michael O'Sullivan , Diego Ruano

This paper investigates practical coding schemes for Distributed Hypothesis Testing (DHT). While the literature has extensively analyzed the information-theoretic performance of DHT and established bounds on Type-II error exponents through…

Information Theory · Computer Science 2024-05-14 Elsa Dupraz , Ismaila Salihou Adamou , Reza Asvadi , Tad Matsumoto

Hashing produces compact representations for documents, to perform tasks like classification or retrieval based on these short codes. When hashing is supervised, the codes are trained using labels on the training data. This paper first…

Computer Vision and Pattern Recognition · Computer Science 2017-08-11 Alexandre Sablayrolles , Matthijs Douze , Hervé Jégou , Nicolas Usunier

The method of random projections has become very popular for large-scale applications in statistical learning, information retrieval, bio-informatics and other applications. Using a well-designed coding scheme for the projected data, which…

Machine Learning · Computer Science 2013-08-12 Ping Li , Michael Mitzenmacher , Anshumali Shrivastava

Determining the exact decoding error probability of linear block codes is an interesting problem. For binary BCH codes, McEliece derived methods to estimate the error probability of a simple bounded distance decoding (BDD) for BCH codes.…

Information Theory · Computer Science 2026-01-29 Sisi Miao , Jonathan Mandelbaum , Holger Jäkel , Laurent Schmalen

Large-scale, fault-tolerant quantum computations will be enabled by quantum error-correcting codes (QECC). This work presents the first systematic technique to test the accuracy and effectiveness of different QECC decoding schemes by…

Quantum Physics · Physics 2023-11-22 Arshpreet Singh Maan , Alexandru Paler

Sparse coding is a crucial subroutine in algorithms for various signal processing, deep learning, and other machine learning applications. The central goal is to learn an overcomplete dictionary that can sparsely represent a given input…

Machine Learning · Statistics 2017-12-14 Thanh V. Nguyen , Raymond K. W. Wong , Chinmay Hegde

We give a decoding algorithm for a class of error-correcting codes, which can be used in the DHH-cryptosystem, which is a candidate for post-quantum cryptography, since it is of McEliece type. Furthermore, we implement the encryption and…

Cryptography and Security · Computer Science 2023-03-20 Carolin Hannusch , Giuseppe Filippone

We propose a unified methodology to analyse the performance of caches (both isolated and interconnected), by extending and generalizing a decoupling technique originally known as Che's approximation, which provides very accurate results at…

Networking and Internet Architecture · Computer Science 2016-02-26 Valentina Martina , Michele Garetto , Emilio Leonardi

In this paper, we propose a methodology to compute the optimal finite-length coding rate for random linear network coding schemes over a line network. To do so, we first model the encoding, reencoding, and decoding process of different…

Networking and Internet Architecture · Computer Science 2018-05-16 Tan Do-Duy , M. Ángeles Vázquez-Castro

Much progress has been made on decoding algorithms for error-correcting codes in the last decade. In this article, we give an introduction to some fundamental results on iterative, message-passing algorithms for low-density parity check…

Information Theory · Computer Science 2007-07-16 Venkatesan Guruswami

The design of low-density parity-check (LDPC) code ensembles optimized for a finite number of decoder iterations is investigated. Our approach employs EXIT chart analysis and differential evolution to design such ensembles for the binary…

Information Theory · Computer Science 2016-11-17 Ian P. Mulholland , Enrico Paolini , Mark F. Flanagan

We consider binary systematic network codes and investigate their capability of decoding a source message either in full or in part. We carry out a probability analysis, derive closed-form expressions for the decoding probability and show…

Information Theory · Computer Science 2016-11-15 Andrew L. Jones , Ioannis Chatzigeorgiou , Andrea Tassi

Hash coding has been widely used in the approximate nearest neighbor search for large-scale image retrieval. Recently, many deep hashing methods have been proposed and shown largely improved performance over traditional…

Computer Vision and Pattern Recognition · Computer Science 2019-10-18 Zheng Zhang , Qin Zou , Yuewei Lin , Long Chen , Song Wang

In this letter, we evaluate the finite-length performance of network coding when using either random or structured encoding matrices. First, we present our novel construction of structured network codes over Fq (q = 2^m) using Pascal…

Networking and Internet Architecture · Computer Science 2019-11-28 Tan Do-Duy , M. Angeles Vazquez-Castro

This dissertation introduces measurement-based performance modeling and prediction techniques for dense linear algebra algorithms. As a core principle, these techniques avoid executions of such algorithms entirely, and instead predict their…

Performance · Computer Science 2017-06-06 Elmar Peise

Providing closed-form estimates of the decoding failure rate of iterative decoders for low- and moderate-density binary parity-check codes has attracted significant interest in the research community. Recently, interest in this topic has…

Cryptography and Security · Computer Science 2026-02-02 Alessandro Annechini , Alessandro Barenghi , Gerardo Pelosi

We propose theoretical and empirical improvements for two-stage hashing methods. We first provide a theoretical analysis on the quality of the binary codes and show that, under mild assumptions, a residual learning scheme can construct…

Machine Learning · Computer Science 2018-08-07 Fatih Cakir , Kun He , Stan Sclaroff

Secure codes are widely-studied combinatorial structures which were introduced for traitor tracing in broadcast encryption. To determine the maximum size of such structures is the main research objective. In this paper, we investigate the…

Information Theory · Computer Science 2021-08-24 Bingchen Qian , Xin Wang , Gennian Ge

Soft-decision decoding is NP-hard problem of great interest to developers of communication system. We present an efficient soft-decision decoding of linear block codes based on compact genetic algorithm (cGA) and compare its performance…

Information Theory · Computer Science 2012-11-26 Ahmed Azouaoui , Ahlam Berkani , Mostafa Belkasmi