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Fawzi and Fawzi recently defined the sharp R\'enyi divergence, $D_\alpha^\#$, for $\alpha \in (1, \infty)$, as an additional quantum R\'enyi divergence with nice mathematical properties and applications in quantum channel discrimination and…

Quantum Physics · Physics 2021-10-12 Bjarne Bergh , Robert Salzmann , Nilanjana Datta

We derive a new variational formula for the R\'enyi family of divergences, $R_\alpha(Q\|P)$, between probability measures $Q$ and $P$. Our result generalizes the classical Donsker-Varadhan variational formula for the Kullback-Leibler…

Machine Learning · Statistics 2021-07-21 Jeremiah Birrell , Paul Dupuis , Markos A. Katsoulakis , Luc Rey-Bellet , Jie Wang

Lossy transmission over a relay channel in which the relay has access to correlated side information is considered. First, a joint source-channel decode-and-forward scheme is proposed for general discrete memoryless sources and channels.…

Information Theory · Computer Science 2016-11-17 Deniz Gunduz , Elza Erkip , Andrea J. Goldsmith , H. Vincent Poor

Shannon's information theory deliberately excludes message semantics. This paper develops a rigorous framework for semantic communication that integrates formal proof systems with Shannon-theoretic tools. We introduce an axiomatic…

Logic in Computer Science · Computer Science 2026-04-21 Jianfeng Xu

The process of state preparation, its transmission and subsequent measurement can be classically simulated through the communication of some amount of classical information. Recently, we proved that the minimal communication cost is the…

Quantum Physics · Physics 2014-01-17 Alberto Montina , Stefan Wolf

We prove the large deviation principle for several entropy and cross entropy estimators based on return times and waiting times on shift spaces over finite alphabets. We consider shift-invariant probability measures satisfying some…

Probability · Mathematics 2024-08-07 Noé Cuneo , Renaud Raquépas

In this work, the problem of communicating decisions of a classifier over a noisy channel is considered. With machine learning based models being used in variety of time-sensitive applications, transmission of these decisions in a reliable…

Information Theory · Computer Science 2024-04-24 Noel Teku , Sudarshan Adiga , Ravi Tandon

One of the basic tenets in information theory, the data processing inequality states that output divergence does not exceed the input divergence for any channel. For channels without input constraints, various estimates on the amount of…

Information Theory · Computer Science 2015-08-14 Yury Polyanskiy , Yihong Wu

A secrecy system with side information at the decoders is studied in the context of lossy source compression over a noiseless broadcast channel. The decoders have access to different side information sequences that are correlated with the…

Information Theory · Computer Science 2014-10-07 Eva C. Song , Paul Cuff , H. Vincent Poor

We determine the exact strong converse exponent of classical-quantum channel coding, for every rate above the Holevo capacity. Our form of the exponent is an exact analogue of Arimoto's, given as a transform of the Renyi capacities with…

Quantum Physics · Physics 2018-07-10 Milan Mosonyi , Tomohiro Ogawa

The Shannon lower bound is one of the few lower bounds on the rate-distortion function that holds for a large class of sources. In this paper, it is demonstrated that its gap to the rate-distortion function vanishes as the allowed…

Information Theory · Computer Science 2016-11-17 Tobias Koch

This paper proposes a revised definition for the entanglement cost of a quantum channel $\mathcal{N}$. In particular, it is defined here to be the smallest rate at which entanglement is required, in addition to free classical communication,…

Quantum Physics · Physics 2023-01-18 Mark M. Wilde

This paper finds new tight finite-blocklength bounds for the best achievable lossy joint source-channel code rate, and demonstrates that joint source-channel code design brings considerable performance advantage over a separate one in the…

Information Theory · Computer Science 2014-02-05 Victoria Kostina , Sergio Verdú

In presence of sparse noise we propose kernel regression for predicting output vectors which are smooth over a given graph. Sparse noise models the training outputs being corrupted either with missing samples or large perturbations. The…

Machine Learning · Statistics 2018-11-07 Arun Venkitaraman , Pascal Frossard , Saikat Chatterjee

Recursion is a fundamental concept in the design of filters and audio systems. In particular, artificial reverberation systems that use delay networks depend on recursive paths to control both echo density and the decay rate of modal…

Audio and Speech Processing · Electrical Eng. & Systems 2026-04-28 Gloria Dal Santo , Karolina Prawda , Sebastian J. Schlecht , Vesa Välimäki

In information theory -- as well as in the adjacent fields of statistics, machine learning, artificial intelligence, signal processing and pattern recognition -- many flexibilizations of the omnipresent Kullback-Leibler information distance…

Information Theory · Computer Science 2022-11-16 Michel Broniatowski , Wolfgang Stummer

We study two problems. First, we consider the large deviation behavior of empirical measures of certain diffusion processes as, simultaneously, the time horizon becomes large and noise becomes vanishingly small. The law of large numbers…

Probability · Mathematics 2023-09-14 Amarjit Budhiraja , Pavlos Zoubouloglou

Direct evaluation of the rate-distortion function has rarely been achieved when it is strictly greater than its Shannon lower bound. In this paper, we consider the rate-distortion function for the distortion measure defined by an…

Information Theory · Computer Science 2013-02-27 Kazuho Watanabe

The sandwiched R\'enyi divergences of two finite-dimensional density operators quantify their asymptotic distinguishability in the strong converse domain. This establishes the sandwiched R\'enyi divergences as the operationally relevant…

Quantum Physics · Physics 2025-08-12 Milán Mosonyi

This paper analyzes the outage probability of orthogonal time frequency space (OTFS) modulation under a lossy communication scenario. First of all, we introduce the channel model and the vector form representation of OTFS this paper uses.…

Information Theory · Computer Science 2024-10-03 Xin Zhang , Wensheng Lin , Lixin Li , Fucheng Yang , Zhu Han , Tad Matsumoto