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This work investigates binary hypothesis testing between $H_0\sim P_0$ and $H_1\sim P_1$ in the finite-sample regime under asymmetric error constraints. By employing the ``reverse" R\'enyi divergence, we derive novel non-asymptotic bounds…

Information Theory · Computer Science 2026-01-21 Roberto Bruno , Adrien Vandenbroucque , Amedeo Roberto Esposito

This paper considers guessing-based decoders with abandonment for discrete memoryless channels in which all codewords have the same composition. This class of decoders rank-orders all input sequences in the codebook's composition class from…

Information Theory · Computer Science 2025-08-11 Vincent Y. F. Tan , Hamdi Joudeh

This paper applies error-exponent and dispersion-style analyses to derive finite-blocklength achievability bounds for low-density parity-check (LDPC) codes over the point-to-point channel (PPC) and multiple access channel (MAC). The…

Information Theory · Computer Science 2020-05-14 Yuxin Liu , Michelle Effros

The source-coding problem with side information at the decoder is studied subject to a constraint that the encoder---to whom the side information is unavailable---be able to compute the decoder's reconstruction sequence to within some…

Information Theory · Computer Science 2016-11-15 Amos Lapidoth , Andreas Malär , Michèle Wigger

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

For several styles of fidelity constraints -- guaranteed distortion, conditional excess distortion, excess distortion -- we show mutual information upper bounds on the minimum expected description length needed to represent a random…

Information Theory · Computer Science 2026-02-10 Victoria Kostina

We study error exponents for the problem of low-rate communication over a directed graph, where each edge in the graph represents a noisy communication channel, and there is a single source and destination. We derive maxflow-based…

Information Theory · Computer Science 2023-04-06 Yan Hao Ling , Jonathan Scarlett

Quantum entanglement can be used in a communication scheme to establish a correlation between successive channel inputs that is impossible by classical means. It is known that the classical capacity of quantum channels can be enhanced by…

Quantum Physics · Physics 2018-04-17 Dawei Ding , Mark M. Wilde

We consider the problem of source compression under three different scenarios in the one-shot (non- asymptotic) regime. To be specific, we prove one-shot achievability and converse bounds on the coding rates for distributed source coding,…

Information Theory · Computer Science 2015-12-11 Naqueeb Ahmad Warsi

Recent advances in machine learning-aided lossy compression are incorporating perceptual fidelity into the rate-distortion theory. In this paper, we study the rate-distortion-perception trade-off when the perceptual quality is measured by…

Information Theory · Computer Science 2023-05-23 Xueyan Niu , Deniz Gündüz , Bo Bai , Wei Han

In this paper, we study the problem of relaying a single bit over a tandem of binary-input channels, with the goal of attaining the highest possible error exponent in the exponentially decaying error probability. Our previous work gave an…

Information Theory · Computer Science 2024-06-07 Yan Hao Ling , Jonathan Scarlett

We consider random interlacements on $ \mathbb{Z}^d$, $d \ge 3$, when their vacant set is in a strongly percolative regime. Given a large box centered at the origin, we establish an asymptotic upper bound on the exponential rate of decay of…

Probability · Mathematics 2021-11-03 Alain-Sol Sznitman

For variable-length coding with an almost-sure distortion constraint, Zhang et al. show that for discrete sources the redundancy is upper bounded by $\log n/n$ and lower bounded (in most cases) by $\log n/(2n)$, ignoring lower order terms.…

Information Theory · Computer Science 2026-01-21 Sharang M. Sriramu , Aaron B. Wagner

Error exponents characterize the exponential decay, when increasing message length, of the probability of error of many error-correcting codes. To tackle the long standing problem of computing them exactly, we introduce a general,…

Disordered Systems and Neural Networks · Physics 2007-07-16 Thierry Mora , Olivier Rivoire

It is well known that independent (separate) encoding of K correlated sources may incur some rate loss compared to joint encoding, even if the decoding is done jointly. This loss is particularly evident in the multiple descriptions problem,…

Information Theory · Computer Science 2022-05-23 Jan Østergaard , Uri Erez , Ram Zamir

In continuation to an earlier work, where error exponents of typical random codes were studied in the context of general block coding, with no underlying structure, here we carry out a parallel study on typical random, time-varying trellis…

Information Theory · Computer Science 2019-03-05 Neri Merhav

Sparse representation has been applied successfully in abnormal event detection, in which the baseline is to learn a dictionary accompanied by sparse codes. While much emphasis is put on discriminative dictionary construction, there are no…

Computer Vision and Pattern Recognition · Computer Science 2016-03-15 Huamin Ren , Hong Pan , Søren Ingvor Olsen , Thomas B. Moeslund

The linear inverse source and scattering problems are studied from the perspective of compressed sensing, in particular the idea that sufficient incoherence and sparsity guarantee uniqueness of the solution. By introducing the sensor as…

Data Analysis, Statistics and Probability · Physics 2009-05-19 Albert Fannjiang , Pengchong Yan , Thomas Strohmer

For a discrete memoryless channel with finite input and output alphabets, we prove convergence of a parametric family of iterative computations of the optimal correct-decoding exponent. The exponent, as a function of communication rate, is…

Information Theory · Computer Science 2020-05-18 Sergey Tridenski , Anelia Somekh-Baruch , Ram Zamir

We establish the first information-theoretic limits for multimodal retrieval. Casting ranking as lossy source coding, we derive a single-letter rate-distortion function $R(D)$ for reciprocal-rank distortion and prove a converse bound that…

Information Theory · Computer Science 2025-09-16 Thomas Y. Chen
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