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Deep neural networks have shown incredible performance for inference tasks in a variety of domains. Unfortunately, most current deep networks are enormous cloud-based structures that require significant storage space, which limits scaling…

Information Theory · Computer Science 2020-03-10 Sourya Basu , Lav R. Varshney

Publicly available, large pretrained LanguageModels (LMs) generate text with remarkable quality, but only sequentially from left to right. As a result, they are not immediately applicable to generation tasks that break the unidirectional…

Computation and Language · Computer Science 2021-12-28 Peter West , Ximing Lu , Ari Holtzman , Chandra Bhagavatula , Jena Hwang , Yejin Choi

We define multilevel text normalization as sequence-to-sequence processing that transforms naturally noisy text into a sequence of normalized units of meaning (morphemes) in three steps: 1) writing normalization, 2) lemmatization, 3)…

Computation and Language · Computer Science 2019-04-01 Tatyana Ruzsics , Tanja Samardžić

The number of random bits required to approximate a target distribution in terms of un-normalized informational divergence is considered. It is shown that for a variable-to-variable length encoder, this number is lower bounded by the…

Information Theory · Computer Science 2013-08-02 Georg Böcherer , Rana Ali Amjad

The problem of joint universal source coding and identification is considered in the setting of fixed-rate lossy coding of continuous-alphabet memoryless sources. For a wide class of bounded distortion measures, it is shown that any…

Information Theory · Computer Science 2007-07-13 Maxim Raginsky

We consider a setting of Slepian--Wolf coding, where the random bin of the source vector undergoes channel coding, and then decoded at the receiver, based on additional side information, correlated to the source. For a given distribution of…

Information Theory · Computer Science 2016-01-26 Neri Merhav

Several applications in communication, control, and learning require approximating target distributions to within small informational divergence (I-divergence). The additional requirement of invertibility usually leads to using encoders…

Information Theory · Computer Science 2020-10-22 Patrick Schulte , Rana Ali Amjad , Thomas Wiegart , Gerhard Kramer

Linear computation coding is concerned with the compression of multidimensional linear functions, i.e. with reducing the computational effort of multiplying an arbitrary vector to an arbitrary, but known, constant matrix. This paper…

Information Theory · Computer Science 2025-07-02 Hans Rosenberger , Johanna S. Fröhlich , Ali Bereyhi , Ralf R. Müller

Distributed source coding is traditionally viewed in the block coding context -- all the source symbols are known in advance at the encoders. This paper instead considers a streaming setting in which iid source symbol pairs are revealed to…

Information Theory · Computer Science 2007-07-13 Cheng Chang , Stark Draper , Anant Sahai

This paper considers the problem of data compression for dependent quantum systems. It is the second in a series under the same title. As in the previous paper, we are interested in Lempel--Ziv encoding for quantum Gibbs ensembles. Here, we…

Mathematical Physics · Physics 2011-11-09 Oliver Johnson , Yuri Suhov

In this paper, a new method for decoding Low Density Parity Check (LDPC) codes, based on Multi-Layer Perceptron (MLP) neural networks is proposed. Due to the fact that in neural networks all procedures are processed in parallel, this method…

Information Theory · Computer Science 2014-11-14 Alireza Karami , Mahmoud Ahmadian Attari

An ultra-high throughput low-density parity check (LDPC) decoder with an unrolled full-parallel architecture is proposed, which achieves the highest decoding throughput compared to previously reported LDPC decoders in the literature. The…

A pattern of a sequence is a sequence of integer indices with each index describing the order of first occurrence of the respective symbol in the original sequence. In a recent paper, tight general bounds on the block entropy of patterns of…

Information Theory · Computer Science 2007-11-15 Gil I. Shamir

We provide a novel achievability proof of the Slepian-Wolf theorem for i.i.d. sources over finite alphabets. We demonstrate that random codes that are linear over the real field achieve the classical Slepian-Wolf rate-region. For finite…

Information Theory · Computer Science 2008-10-09 Bikash Kumar Dey , Sidharth Jaggi , Michael Langberg

This paper deals with a universal coding problem for a certain kind of multiterminal source coding system that we call the complementary delivery coding system. In this system, messages from two correlated sources are jointly encoded, and…

Information Theory · Computer Science 2007-10-24 Akisato Kimura , Tomohiko Uyematsu , Shigeaki Kuzuoka

Random access to highly compressed strings -- represented by straight-line programs or Lempel-Ziv parses, for example -- is a well-studied topic. Random access to such strings in strongly sublogarithmic time is impossible in the worst case,…

Data Structures and Algorithms · Computer Science 2026-02-05 Ferdinando Cicalese , Zsuzsanna Lipták , Travis Gagie , Gonzalo Navarro , Nicola Prezza , Cristian Urbina

The Block Tree is a recently proposed data structure that reaches compression close to Lempel-Ziv while supporting efficient direct access to text substrings. In this paper we show how a self-index can be built on top of a Block Tree so…

Data Structures and Algorithms · Computer Science 2017-10-11 Gonzalo Navarro

In this paper, we consider a few iterative decoding schemes for the joint source-channel coding of correlated sources. Specifically, we consider the joint source-channel coding of two erasure correlated sources with transmission over…

Information Theory · Computer Science 2009-10-08 Arvind Yedla , Henry D. Pfister , Krishna R. Narayanan

We present a new information-theoretic definition and associated results, based on list decoding in a source coding setting. We begin by presenting list-source codes, which naturally map a key length (entropy) to list size. We then show…

Information Theory · Computer Science 2012-10-09 Flavio du Pin Calmon , Muriel Médard , Linda M. Zeger , João Barros , Mark M. Christiansen , Ken. R. Duffy

The aim of this note is to provide some reference facts for LZW---mostly from Thomas and Cover \cite{Cover:2006aa} and provide a reference for some metrics that can be derived from it. LZW is an algorithm to compute a Kolmogorov Complexity…

Information Theory · Computer Science 2017-08-01 Giulio Ruffini