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The Renyi entropy is a generalisation of the Shannon entropy that is sensitive to the fine details of a probability distribution. We present results for the Renyi entropy of the totally asymmetric exclusion process (TASEP). We calculate…

Statistical Mechanics · Physics 2017-11-10 Anthony J. Wood , Richard A. Blythe , Martin R. Evans

We consider the maximum entropy problems associated with R\'enyi $Q$-entropy, subject to two kinds of constraints on expected values. The constraints considered are a constraint on the standard expectation, and a constraint on the…

Information Theory · Computer Science 2008-12-18 Jean-François Bercher

We prove that all R\'enyi entanglement entropies of spin-chains described by generic (gapped), translational invariant matrix product states (MPS) are extensive for disconnected sub-systems: All R\'enyi entanglement entropy densities of the…

Quantum Physics · Physics 2020-08-31 Alberto Rolandi , Henrik Wilming

We present a general method for calculating R\'enyi entropies in the ground state of a one-dimensional critical system with mixed open boundaries, for an interval starting at one of its ends. In the conformal field theory framework, this…

Statistical Mechanics · Physics 2025-11-12 Benoit Estienne , Yacine Ikhlef , Andrei Rotaru

We revisit the outlier hypothesis testing framework of Li \emph{et al.} (TIT 2014) and derive fundamental limits for the optimal test. In outlier hypothesis testing, one is given multiple observed sequences, where most sequences are…

Statistics Theory · Mathematics 2022-05-17 Lin Zhou , Yun Wei , Alfred Hero

R\'enyi divergences play a pivotal role in information theory, statistics, and machine learning. While several estimators of these divergences have been proposed in the literature with their consistency properties established and minimax…

Information Theory · Computer Science 2025-09-12 Sreejith Sreekumar , Kengo Kato

The generalized Poor-Verdu error lower bound for multihypothesis testing is revisited. Its asymptotic expression is established in closed-form as its tilting parameter grows to infinity. It is also shown that the asymptotic generalized…

Information Theory · Computer Science 2020-01-07 Ling-Hua Chang , Po-Ning Chen , Fady Alajaji , Yunghsiang S. Han

We derive a strengthened monotonicity inequality for quantum relative entropy by employing properties of $\alpha$-R\'{e}nyi relative entropy. We develop a unifying treatment towards the improvement of some quantum entropy inequalities. In…

Quantum Physics · Physics 2016-03-21 Lin Zhang

Error probabilities of random codes for memoryless channels are considered in this paper. In the area of communication systems, admissible error probability is very small and it is sometimes more important to discuss the relative gap…

Information Theory · Computer Science 2015-06-11 Junya Honda

In parametric Bayesian learning, a prior is assumed on the parameter $W$ which determines the distribution of samples. In this setting, Minimum Excess Risk (MER) is defined as the difference between the minimum expected loss achievable when…

Machine Learning · Computer Science 2021-07-20 Hassan Hafez-Kolahi , Behrad Moniri , Shohreh Kasaei , Mahdieh Soleymani Baghshah

Will further scaling up of machine learning models continue to bring success? A significant challenge in answering this question lies in understanding generalization gap, which is the impact of overfitting. Understanding generalization gap…

Machine Learning · Statistics 2026-05-18 Atsushi Suzuki , Jing Wang

In this paper we obtain new bounds for the minimum output entropies of random quantum channels. These bounds rely on random matrix techniques arising from free probability theory. We then revisit the counterexamples developed by Hayden and…

Probability · Mathematics 2015-02-12 Benoît Collins , Ion Nechita

This paper explores some applications of a two-moment inequality for the integral of the $r$-th power of a function, where $0 < r< 1$. The first contribution is an upper bound on the R\'{e}nyi entropy of a random vector in terms of the two…

Information Theory · Computer Science 2017-02-24 Galen Reeves

We consider the problem of approximating the empirical Shannon entropy of a high-frequency data stream under the relaxed strict-turnstile model, when space limitations make exact computation infeasible. An equivalent measure of entropy is…

Computation · Statistics 2013-04-18 Peter Clifford , Ioana Ada Cosma

Minimum Bayes-risk (MBR) decoding has recently gained renewed attention in text generation. MBR decoding considers texts sampled from a model as pseudo-references and selects the text with the highest similarity to the others. Therefore,…

Computation and Language · Computer Science 2024-04-02 Atsumoto Ohashi , Ukyo Honda , Tetsuro Morimura , Yuu Jinnai

Quantifying the complexity and irregularity of time series data is a primary pursuit across various data-scientific disciplines. Sample entropy (SampEn) is a widely adopted metric for this purpose, but its reliability is sensitive to the…

Applications · Statistics 2024-05-13 Zachary Blanks , Donald E. Brown

In this paper, new classes of lower bounds on the outage error probability and on the mean-square-error (MSE) in Bayesian parameter estimation are proposed. The minima of the h-outage error probability and the MSE are obtained by the…

Information Theory · Computer Science 2010-05-05 Routtenberg Tirza , Joseph Tabrikian

We investigate quantum R\'enyi entropic quantities, specifically those derived from 'sandwiched' divergence. This divergence is one of several proposed R\'enyi generalisations of the quantum relative entropy. We may define R\'enyi…

Quantum Physics · Physics 2021-10-04 Alexander McKinlay

PAE cannot be made a basis for either a generalized statistical mechanics or a generalized information theory. Either statistical independence must be waived, or the expression of the averaged conditional probability as the difference…

Statistical Mechanics · Physics 2011-10-25 B. H. Lavenda

We consider the problem of modulation and estimation of a random parameter $U$ to be conveyed across a discrete memoryless channel. Upper and lower bounds are derived for the best achievable exponential decay rate of a general moment of the…

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