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The recently successful Munchausen Reinforcement Learning (M-RL) features implicit Kullback-Leibler (KL) regularization by augmenting the reward function with logarithm of the current stochastic policy. Though significant improvement has…

Machine Learning · Computer Science 2022-05-17 Lingwei Zhu , Zheng Chen , Eiji Uchibe , Takamitsu Matsubara

The equilibrium distributions of probabilities providing maximality of Renyi and Tsallis entropies are rederived. New S-forms of them are found which are normalised with corresponding entropies in contrast to the usual Z-forms normalised…

Statistical Mechanics · Physics 2007-05-23 A. G. Bashkirov

The construction of efficient and effective decision trees remains a key topic in machine learning because of their simplicity and flexibility. A lot of heuristic algorithms have been proposed to construct near-optimal decision trees. ID3,…

Machine Learning · Statistics 2016-08-24 Yisen Wang , Chaobing Song , Shu-Tao Xia

In this work, we derive information-theoretic properties for a modified Tsallis entropy, hereinafter referred to as q-entropy. We introduce the notions of joint q-entropy, conditional q-entropy, relative q-entropy, conditional mutual…

Mathematical Physics · Physics 2026-03-31 Marco A. S. Trindade

We demonstrate and discuss the process of gaining information and show an example in which some specific way of gaining information about an object results in the Tsallis form of entropy rather than in the Shannon one.

Statistical Mechanics · Physics 2009-11-13 Grzegorz Wilk , Zbigniew Wlodarczyk

In this paper we derived a 6N dimensional non-homogeneous evolution equation of Tsallis non-equilibrium entropy; presented a formula for entropy production rate (i.e. the law of entropy increase) for Tsallis entropy only when its index q>0,…

Statistical Mechanics · Physics 2014-06-10 Xing Xiu-San

This article proposes a new two-parameter generalized entropy, which can be reduced to the Tsallis and the Shannon entropy for specific values of its parameters. We develop a number of information-theoretic properties of this generalized…

Mathematical Physics · Physics 2024-05-02 Supriyo Dutta , Shigeru Furuichi , Partha Guha

In the previous paper \cite{FYK}, we mainly studied the mathematical properties of Tsallis relative entropy with respect to the density operators. As an application of it, we adopt a parametrically extended entanglement-measure due to…

Quantum Physics · Physics 2010-01-08 Shigeru Furuichi

The maximum entropy principle is often used for bi-level or multi-level thresholding of images. For this purpose, some methods are available based on Shannon and Tsallis entropies. In this paper, we discuss them and propose a method based…

Computer Vision and Pattern Recognition · Computer Science 2015-08-06 Amelia Carolina Sparavigna

We revisit the well-studied problem of estimating the Shannon entropy of a probability distribution, now given access to a probability-revealing conditional sampling oracle. In this model, the oracle takes as input the representation of a…

Cryptography and Security · Computer Science 2022-06-03 Priyanka Golia , Brendan Juba , Kuldeep S. Meel

In density estimation task, maximum entropy model (Maxent) can effectively use reliable prior information via certain constraints, i.e., linear constraints without empirical parameters. However, reliable prior information is often…

Machine Learning · Computer Science 2010-04-08 Yuexian Hou , Tingxu Yan , Peng Zhang , Dawei Song , Wenjie Li

We demonstrate that dual entropy expressions of the Tsallis type apply naturally to statistical-mechanical systems that experience an exceptional contraction of their configuration space. The entropic index $\alpha>1$ describes the…

Chaotic Dynamics · Physics 2015-11-30 G. Cigdem Yalcin , Carlos Velarde , Alberto Robledo

This study derived the vertical distribution of streamwise velocity in wide open channels by maximizing Tsallis entropy, in accordance with the maximum entropy principle, subject to the total probability rule and the conservation of mass,…

Computational Physics · Physics 2024-03-04 Manotosh Kumbhakar , Rajendra K. Ray , Suvra Kanti Chakraborty , Koeli Ghoshal , Vijay P. Singh

In this paper, we propose a novel maximum causal Tsallis entropy (MCTE) framework for imitation learning which can efficiently learn a sparse multi-modal policy distribution from demonstrations. We provide the full mathematical analysis of…

Machine Learning · Computer Science 2018-05-29 Kyungjae Lee , Sungjoon Choi , Songhwai Oh

We study the evolution of Tsallis entropy along the heat flow and establish its concavity in arbitrary dimensions. Extending prior results that were restricted to the one-dimensional setting, we prove that the Tsallis entropy is concave in…

Information Theory · Computer Science 2026-04-24 Lukang Sun

We show that Tsallis ensemble of power-law distributions provides a mechanical model of nonextensive equilibrium thermodynamics for small interacting Hamiltonian systems, i.e., using Boltzmann's original nomenclature, we prove that it is an…

Statistical Mechanics · Physics 2007-05-23 M. Campisi , G. B. Bagci

We give the tight bounds of Tsallis relative operator entropy by using Hermite-Hadamard's inequality. Some reverse inequalities related to Young inequalities are also given. In addition, operator inequalities for normalized positive linear…

Functional Analysis · Mathematics 2017-05-08 Hamid Reza Moradi , Shigeru Furuichi , Nicuşor Minculete

This article is a continuation of my paper [arxiv: 1409.1015v2]. R\'enyi and Tsallis entropies are associated to positive linear operators and properties of some functions related to these entropies are investigated.

Classical Analysis and ODEs · Mathematics 2014-12-17 Ioan Raşa

Recently, weighted cumulative residual Tsallis entropy has been introduced in the literature as a generalization of weighted cumulative residual entropy. We study some new properties of weighted cumulative residual Tsallis entropy measure.…

Statistics Theory · Mathematics 2026-02-02 Siddhartha Chakraborty , Asok K. Nanda

Euler turbulence has been experimentally observed to relax to a metaequilibrium state that does not maximize the Boltzmann entropy, but rather seems to minimize enstrophy. We show that a recent generalization of thermodynamics and…

chao-dyn · Physics 2016-08-31 Bruce M. Boghosian