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Learned image compression codecs have recently achieved impressive compression performances surpassing the most efficient image coding architectures. However, most approaches are trained to minimize rate and distortion which often leads to…

Computer Vision and Pattern Recognition · Computer Science 2024-03-06 Daniele Mari , Simone Milani

We establish the fundamental limits of lossless linear analog compression by considering the recovery of random vectors ${\boldsymbol{\mathsf{x}}}\in{\mathbb R}^m$ from the noiseless linear measurements…

Information Theory · Computer Science 2016-05-06 Giovanni Alberti , Helmut Bölcskei , Camillo De Lellis , Günther Koliander , Erwin Riegler

Many information sources are not just sequences of distinguishable symbols but rather have invariances governed by alternative counting paradigms such as permutations, combinations, and partitions. We consider an entire classification of…

Universal variable-to-fixed (V-F) length coding of $d$-dimensional exponential family of distributions is considered. We propose an achievable scheme consisting of a dictionary, used to parse the source output stream, making use of the…

Information Theory · Computer Science 2017-08-02 Nematollah Iri , Oliver Kosut

We introduce a new approach to proving that a sequence of deterministic linear codes achieves capacity on an erasure channel under maximum a posteriori decoding. Rather than relying on the precise structure of the codes our method exploits…

Information Theory · Computer Science 2016-01-19 Shrinivas Kudekar , Santhosh Kumar , Marco Mondelli , Henry D. Pfister , Eren Şaşoğlu , Rüdiger Urbanke

The following critical phenomenon was recently discovered. When a memoryless source is compressed using a variable-length fixed-distortion code, the fastest convergence rate of the (pointwise) compression ratio to the optimal $R(D)$…

Probability · Mathematics 2007-07-13 Amir Dembo , Ioannis Kontoyiannis

A general method of source coding over expansion is proposed in this paper, which enables one to reduce the problem of compressing an analog (continuous-valued source) to a set of much simpler problems, compressing discrete sources.…

Information Theory · Computer Science 2013-08-13 Hongbo Si , O. Ozan Koyluoglu , Sriram Vishwanath

Computing problems that handle large amounts of data necessitate the use of lossless data compression for efficient storage and transmission. We present a novel lossless universal data compression algorithm that uses parallel computational…

Information Theory · Computer Science 2023-07-19 Nikhil Krishnan , Dror Baron

This paper introduces a new approach to proving that a sequence of deterministic linear codes achieves capacity on an erasure channel under maximum a posteriori decoding. Rather than relying on the precise structure of the codes, this…

Information Theory · Computer Science 2015-06-16 Santhosh Kumar , Henry D. Pfister

Motivated by applications in spatial genomics, we revisit group testing (Dorfman~1943) and propose the class of $\lambda$-{\sf ADD}-codes, studying such codes with certain distance $d$ and codelength $n$. When $d$ is constant, we provide…

Information Theory · Computer Science 2024-05-14 Kok Hao Chen , Duc Tu Dao , Han Mao Kiah , Van Long Phuoc Pham , Eitan Yaakobi

Large Speech Language Models (LSLMs) typically operate at high token rates (tokens/s) to ensure acoustic fidelity, yet this results in sequence lengths that far exceed the underlying semantic content, incurring prohibitive inference costs.…

Computation and Language · Computer Science 2026-04-09 Bajian Xiang , Tingwei Guo , Xuan Chen , Yang Han

We study a new encoding scheme for lossy source compression based on spatially coupled low-density generator-matrix codes. We develop a belief-propagation guided-decimation algorithm, and show that this algorithm allows to approach the…

Information Theory · Computer Science 2012-02-23 Vahid Aref , Nicolas Macris , Rudiger Urbanke , Marc Vuffray

The second-order achievable asymptotics in typical random number generation problems such as resolvability, intrinsic randomness, fixed-length source coding are considered. In these problems, several researchers have derived the first-order…

Information Theory · Computer Science 2013-01-01 Ryo Nomura , Te Sun Han

A solution to the problem of asymptotically optimum perfect universal steganography of finite memoryless sources with a passive warden is provided, which is then extended to contemplate a distortion constraint. The solution rests on the…

Information Theory · Computer Science 2017-12-27 Félix Balado , David Haughton

Understanding generalization in modern machine learning settings has been one of the major challenges in statistical learning theory. In this context, recent years have witnessed the development of various generalization bounds suggesting…

Machine Learning · Statistics 2022-07-01 Milad Sefidgaran , Amin Gohari , Gaël Richard , Umut Şimşekli

Solomonoff's central result on induction is that the posterior of a universal semimeasure M converges rapidly and with probability 1 to the true sequence generating posterior mu, if the latter is computable. Hence, M is eligible as a…

Information Theory · Computer Science 2007-08-20 Marcus Hutter , Andrej Muchnik

This paper investigates the general distributed lossless/lossy source coding formulated by Jana and Blahut. Their multi-letter rate-distortion region, an alternative to the region derived by Yang and Qin, is characterized by entropy…

Information Theory · Computer Science 2024-07-08 Jun Muramatsu

In this paper, we bound the rate of linear codes in $\mathbb{F}_q^n$ with the property that any $k\leq q$ codewords are all simultaneously distinct in at least $d_k$ coordinates. For the case of particular interest $q=k=3$ we recover, with…

Information Theory · Computer Science 2025-10-21 Stefano Della Fiore , Marco Dalai

Consider the case where consecutive blocks of N letters of a semi-infinite individual sequence X over a finite-alphabet are being compressed into binary sequences by some one-to-one mapping. No a-priori information about X is available at…

Information Theory · Computer Science 2013-01-25 Jacob Ziv

We consider lossy compression of a binary symmetric source by means of a low-density generator-matrix code. We derive two lower bounds on the rate distortion function which are valid for any low-density generator-matrix code with a given…

Information Theory · Computer Science 2008-04-11 Shrinivas Kudekar , Ruediger Urbanke