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We calculate the limiting behavior of relative Renyi entropy when the first probability distribution is close to the second one in a non-regular location-shift family which is generated by a probability distribution whose support is an…

Probability · Mathematics 2007-06-13 Masahito Hayashi

Shannon and Renyi entropies are quantitative measures of uncertainty in a data set. They are developed by Renyi in the context of entropy theory. These measures have been studied in the case of the multivariate t-distributions. We extend…

Statistics Theory · Mathematics 2019-01-31 Salah H. Abid , Uday J. Quaez

Let $k\in (d,\infty]$ and consider the $k*$-distance $$\|\mu-\nu\|_{k*}:= \sup\Big\{|\mu(f)-\nu(f)|:\ f\in\B_b(\R^d),\ \|f\|_{\tt L^k}:=\sup_{x\in \R^d}\|1_{B(x,1)}f\|_{L^k}\le 1\Big\}$$ between probability measures on $\R^d$. The…

Probability · Mathematics 2025-08-20 Xing Huang , Feng-Yu Wang

The classical result by It\^o on the existence of strong solutions of stochastic differential equations (SDEs) with Lipschitz coefficients can be extended to the case where the drift is only measurable and bounded. These generalizations are…

Probability · Mathematics 2021-10-05 Gunther Leobacher , Michaela Szölgyenyi , Stefan Thonhauser

Under integrability conditions on distribution dependent coefficients, existence and uniqueness are proved for McKean-Vlasov type SDEs with non-degenerate noise. When the coefficients are Dini continuous in the space variable, gradient…

Probability · Mathematics 2018-05-07 Xing Huang , Feng-Yu Wang

The existence and uniqueness of stationary distributions and the exponential convergence in $L^p$-Wasserstein distance are derived for distribution dependent SDEs from associated decoupled equations. To establish the exponential…

Probability · Mathematics 2022-03-14 Shao-Qin Zhang

We propose a new way of defining entropy of a system, which gives a general form which may be nonextensive as Tsallis entropy, but is linearly dependent on component entropies, like Renyi entropy, which is extensive. This entropy has a…

Adaptation and Self-Organizing Systems · Physics 2007-10-11 Fariel Shafee

Relative entropy is a measure of distinguishability for quantum states, and plays a central role in quantum information theory. The family of Renyi entropies generalizes to Renyi relative entropies that include as special cases most entropy…

High Energy Physics - Theory · Physics 2014-12-12 Nima Lashkari

Quantum Renyi relative entropies provide a one-parameter family of distances between density matrices, which generalizes the relative entropy and the fidelity. We study these measures for renormalization group flows in quantum field theory.…

High Energy Physics - Theory · Physics 2018-10-17 Horacio Casini , Raimel Medina , Ignacio Salazar , Gonzalo Torroba

The entropy production rate is a central quantity in non-equilibrium statistical physics, scoring how far a stochastic process is from being time-reversible. In this paper, we compute the entropy production of diffusion processes at…

Statistical Mechanics · Physics 2023-06-19 Lancelot Da Costa , Grigorios A. Pavliotis

We propose a relative entropy gradient sampler (REGS) for sampling from unnormalized distributions. REGS is a particle method that seeks a sequence of simple nonlinear transforms iteratively pushing the initial samples from a reference…

Machine Learning · Statistics 2021-10-07 Xingdong Feng , Yuan Gao , Jian Huang , Yuling Jiao , Xu Liu

A class of estimators of the R\'{e}nyi and Tsallis entropies of an unknown distribution $f$ in $\mathbb{R}^m$ is presented. These estimators are based on the $k$th nearest-neighbor distances computed from a sample of $N$ i.i.d. vectors with…

Statistics Theory · Mathematics 2012-11-16 Nikolai Leonenko , Luc Pronzato , Vippal Savani

By refining a recent result of Xie and Zhang, we prove the exponential ergodicity under a weighted variation norm for singular SDEs with drift containing a local integrable term and a coercive term. This result is then extended to singular…

Probability · Mathematics 2023-03-10 Feng-Yu Wang

We consider the generalized differential entropy of normalized sums of independent and identically distributed (IID) continuous random variables. We prove that the R\'{e}nyi entropy and Tsallis entropy of order $\alpha\ (\alpha>0)$ of the…

Information Theory · Computer Science 2011-06-20 Hongfei Cui , Jianqiang Sun , Yiming Ding

Via constructing an asymptotic coupling by reflection, in this paper we establish uniform-in-time estimates on probability distances for mean-field type SDEs, where the drift terms under consideration are dissipative merely in the long…

Probability · Mathematics 2024-09-26 Jianhai Bao , Jiaqing Hao

We find the value of constants related to constraints in characterization of some known statistical distributions and then we proceed to use the idea behind maximum entropy principle to derive generalized version of this distributions using…

Statistical Mechanics · Physics 2007-05-23 Oscar Sotolongo-Costa , Alejandro Gonzalez Gonzalez , Francois Brouers

We study nonparametric density estimation in non-stationary drift settings. Given a sequence of independent samples taken from a distribution that gradually changes in time, the goal is to compute the best estimate for the current…

Machine Learning · Computer Science 2023-10-31 Alessio Mazzetto , Eli Upfal

A strengthened version of the central limit theorem for discrete random variables is established, relying only on information-theoretic tools and elementary arguments. It is shown that the relative entropy between the standardised sum of…

Probability · Mathematics 2021-06-02 Lampros Gavalakis , Ioannis Kontoyiannis

We establish heat-kernel bounds and regularity estimates for the transition densities of the diffusion associated with the martingale problem corresponding to the generator of a formal multidimensional Brownian SDE with singular drift. As a…

Analysis of PDEs · Mathematics 2026-05-19 Stéphane Menozzi , Stefano Pagliarani

We present simple and computationally efficient nonparametric estimators of R\'enyi entropy and mutual information based on an i.i.d. sample drawn from an unknown, absolutely continuous distribution over $\R^d$. The estimators are…

Machine Learning · Statistics 2010-10-27 Dávid Pál , Barnabás Póczos , Csaba Szepesvári