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Related papers: Lossless Coding with Generalised Criteria

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A new channel coding approach was proposed in [1] for random multiple access communication over the discrete-time memoryless channel. The coding approach allows users to choose their communication rates independently without sharing the…

Information Theory · Computer Science 2016-11-15 Zheng Wang , Jie Luo

The problem of string reconstruction from substring information has found many applications due to its relevance in DNA- and polymer-based data storage. One practically important and challenging paradigm requires reconstructing mixtures of…

Information Theory · Computer Science 2020-10-22 Ryan Gabrys , Srilakshmi Pattabiraman , Olgica Milenkovic

We propose a set of convex low rank inducing norms for a coupled matrices and tensors (hereafter coupled tensors), which shares information between matrices and tensors through common modes. More specifically, we propose a mixture of the…

Machine Learning · Statistics 2018-06-15 Kishan Wimalawarne , Makoto Yamada , Hiroshi Mamitsuka

It was recently shown that spatial coupling of individual low-density parity-check codes improves the belief-propagation threshold of the coupled ensemble essentially to the maximum a posteriori threshold of the underlying ensemble. We…

Information Theory · Computer Science 2011-08-03 Vahid Aref , Rüdiger L. Urbanke

We propose a universal ensemble for random selection of rate-distortion codes, which is asymptotically optimal in a sample-wise sense. According to this ensemble, each reproduction vector, $\hbx$, is selected independently at random under…

Information Theory · Computer Science 2022-12-26 Neri Merhav

The likelihood decoder is a stochastic decoder that selects the decoded message at random, using the posterior distribution of the true underlying message given the channel output. In this work, we study a generalized version of this…

Information Theory · Computer Science 2016-11-17 Neri Merhav

Regularized empirical risk minimization with constrained labels (in contrast to fixed labels) is a remarkably general abstraction of learning. For common loss and regularization functions, this optimization problem assumes the form of a…

Machine Learning · Computer Science 2016-02-23 Iaroslav Shcherbatyi , Bjoern Andres

The study of a machine learning problem is in many ways is difficult to separate from the study of the loss function being used. One avenue of inquiry has been to look at these loss functions in terms of their properties as scoring rules…

Machine Learning · Computer Science 2022-09-02 Zac Cranko , Robert C. Williamson , Richard Nock

In this paper, we investigate completely decomposable rank-metric codes, i.e. rank-metric codes that are the direct sum of 1-dimensional maximum rank distance codes. We study the weight distribution of such codes, characterizing codewords…

Information Theory · Computer Science 2024-06-28 Paolo Santonastaso

We introduce new definitions of universal and superuniversal computable codes, which are based on a code's ability to approximate Kolmogorov complexity within the prescribed margin for all individual sequences from a given set. Such sets of…

Machine Learning · Statistics 2009-04-10 Łukasz Dębowski

Composite minimization is a powerful framework in large-scale convex optimization, based on decoupling of the objective function into terms with structurally different properties and allowing for more flexible algorithmic design. We…

Optimization and Control · Mathematics 2023-02-17 Jelena Diakonikolas , Cristóbal Guzmán

We consider a setup in which Alice selects a pdf $f$ from a set of prescribed pdfs $\mathscr{P}$ and sends a prefix-free codeword $W$ to Bob in order to allow him to generate a single instance of the random variable $X\sim f$. We describe a…

Information Theory · Computer Science 2018-12-11 Cheuk Ting Li , Abbas El Gamal

Compressive sensing aims to recover a high-dimensional sparse signal from a relatively small number of measurements. In this paper, a novel design of the measurement matrix is proposed. The design is inspired by the construction of…

Information Theory · Computer Science 2016-03-22 Xu Chen , Dongning Guo

The concepts of pseudocodeword and pseudoweight play a fundamental role in the finite-length analysis of LDPC codes. The pseudoredundancy of a binary linear code is defined as the minimum number of rows in a parity-check matrix such that…

Information Theory · Computer Science 2014-10-08 Zihui Liu , Jens Zumbrägel , Marcus Greferath , Xin-Wen Wu

Efficient optimal prefix coding has long been accomplished via the Huffman algorithm. However, there is still room for improvement and exploration regarding variants of the Huffman problem. Length-limited Huffman coding, useful for many…

Information Theory · Computer Science 2007-07-13 Michael B. Baer

This thesis makes several significant contributions to the theory of both Regenerating (RG) and Locally Recoverable (LR) codes. The two principal contributions are characterizing the optimal rate of an LR code designed to recover from $t$…

Information Theory · Computer Science 2018-06-13 S. B. Balaji , P. Vijay Kumar

In this paper, we propose a low-rank coordinate descent approach to structured semidefinite programming with diagonal constraints. The approach, which we call the Mixing method, is extremely simple to implement, has no free parameters, and…

Optimization and Control · Mathematics 2026-05-12 Po-Wei Wang , Wei-Cheng Chang , J. Zico Kolter

In this paper, we consider the problem of constructing optimal average-length binary codes under the constraint that each codeword must contain at most $D$ ones, where $D$ is a given input parameter. We provide an $O(n^2D)$-time complexity…

Information Theory · Computer Science 2025-12-03 Roberto Bruno , Roberto De Prisco , Ugo Vaccaro

Traditional error-correcting codes (ECCs) assume a fixed message length, but many scenarios involve ongoing or indefinite transmissions where the message length is not known in advance. For example, when streaming a video, the user should…

Data Structures and Algorithms · Computer Science 2025-04-09 Klim Efremenko , Or Zamir

We introduce a universal quantization scheme based on random coding, and we analyze its performance. This scheme consists of a source-independent random codebook (typically_mismatched_ to the source distribution), followed by optimal…

Information Theory · Computer Science 2007-07-13 Ioannis Kontoyiannis , Rami Zamir
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