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In this work we prove sufficient conditions for the Glauber dynamics corresponding to a sequence of (non-product) measures on finite product spaces to be rapidly mixing, i.e. that the mixing time with respect to the total variation distance…

Probability · Mathematics 2019-02-27 Arthur Sinulis

We provide a general framework for computing upper bounds on mixing times of finite Markov chains when its minimal ideal is left zero. Our analysis is based on combining results by Brown and Diaconis with our previous work on stationary…

Probability · Mathematics 2023-01-04 John Rhodes , Anne Schilling

In the context of interacting particle systems, we study the influence of the action of the semigroup on the concentration property of Lipschitz functions. As an application, this gives a new approach to estimate the relaxation speed to…

Probability · Mathematics 2015-06-30 Jean René Chazottes , Pierre Collet , Frank Redig

We study the convergence properties of the Gibbs Sampler in the context of posterior distributions arising from Bayesian analysis of conditionally Gaussian hierarchical models. We develop a multigrid approach to derive analytic expressions…

Computation · Statistics 2019-06-27 Giacomo Zanella , Gareth Roberts

For any stationary $\mZ^d$-Gibbs measure that satisfies strong spatial mixing, we obtain sequences of upper and lower approximations that converge to its entropy. In the case, $d=2$, these approximations are efficient in the sense that the…

Dynamical Systems · Mathematics 2012-08-09 Brian Marcus , Ronnie Pavlov

The popularity of Adaptive MCMC has been fueled on the one hand by its success in applications, and on the other hand, by mathematically appealing and computationally straightforward optimisation criteria for the Metropolis algorithm…

Computation · Statistics 2018-01-30 Cyril Chimisov , Krzysztof Latuszynski , Gareth Roberts

We consider various versions of adaptive Gibbs and Metropolis-within-Gibbs samplers, which update their selection probabilities (and perhaps also their proposal distributions) on the fly during a run by learning as they go in an attempt to…

Computation · Statistics 2013-02-28 Krzysztof Łatuszyński , Gareth O. Roberts , Jeffrey S. Rosenthal

We continue our study of exponential law for occurrences and returns of patterns in the context of Gibbsian random fields. For the low temperature plus phase of the Ising model, we prove exponential laws with error bounds for occurrence,…

Mathematical Physics · Physics 2007-05-23 J. -R. Chazottes , F. Redig

We present a new notion of probabilistic duality for random variables involving mixture distributions. Using this notion, we show how to implement a highly-parallelizable Gibbs sampler for weakly coupled discrete pairwise graphical models…

Machine Learning · Computer Science 2016-11-23 Lars Mescheder , Sebastian Nowozin , Andreas Geiger

We study the mixing time of Metropolis-Adjusted Langevin algorithm (MALA) for sampling a target density on $\mathbb{R}^d$. We assume that the target density satisfies $\psi_\mu$-isoperimetry and that the operator norm and trace of its…

Machine Learning · Statistics 2023-06-09 Yuansi Chen , Khashayar Gatmiry

We extend several Cheeger-type isoperimetric bounds for convex sets in Euclidean space, due to Bobkov and Kannan-Lov\'asz-Simonovits, to Riemannian manifolds having non-negative Ricci curvature. In order to extend Bobkov's bound, we require…

Functional Analysis · Mathematics 2011-05-06 Emanuel Milman

This report is dedicated to the construction and analysis of so-called Generalized Impedance Boundary Conditions (GIBCs) used in electromagnetic scattering problems from imperfect conductors as higher order approximations of a perfect…

Analysis of PDEs · Mathematics 2008-01-07 Houssem Haddar , Patrick Joly , Hoai Minh Nguyen

We prove an upper bound of $1.5324 n \log n$ for the mixing time of the random-to-random insertion shuffle, improving on the best known upper bound of $2 n \log n$. Our proof is based on the analysis of a non-Markovian coupling.

Probability · Mathematics 2014-12-02 Ben Morris , Chuan Qin

In this paper, we present a novel approach to fitting mixture models based on estimating first the posterior distribution of the auxiliary variables that assign each observation to a group in the mixture. The posterior distributions of the…

Computation · Statistics 2017-12-29 Virgilio Gomez-Rubio

A key task in Bayesian statistics is sampling from distributions that are only specified up to a partition function (i.e., constant of proportionality). However, without any assumptions, sampling (even approximately) can be #P-hard, and few…

Machine Learning · Computer Science 2018-12-03 Rong Ge , Holden Lee , Andrej Risteski

We give a near-linear time sampler for the Gibbs distribution of the ferromagnetic Ising models with edge activities $\boldsymbol{\beta} > 1$ and external fields $\boldsymbol{\lambda}<1$ (or symmetrically, $\boldsymbol{\lambda}>1$) on…

Probability · Mathematics 2023-08-21 Xiaoyu Chen , Xinyuan Zhang

Disagreement percolation connects a Gibbs lattice gas and i.i.d. site percolation on the same lattice such that non-percolation implies uniqueness of the Gibbs measure. This work generalises disagreement percolation to the hard-sphere model…

Probability · Mathematics 2019-07-02 Christoph Hofer-Temmel

We study the spectral gaps of parallel and simulated tempering chains targeting multimodal Gibbs measures. In particular, we consider chains constructed from Metropolis random walks that preserve the Gibbs distributions at a sequence of…

Probability · Mathematics 2026-04-07 Seungjae Son

We study the mixing time of Glauber dynamics on monotone systems. For monotone systems satisfying the entropic independence condition, we prove a new mixing time comparison result for Glauber dynamics. For concrete applications, we obtain…

Discrete Mathematics · Computer Science 2025-07-16 Weiming Feng , Minji Yang

We develop a new framework for deriving time-uniform concentration bounds for the output of stochastic sequential algorithms satisfying certain recursive inequalities akin to those defining the almost-supermartingale processes introduced by…

Statistics Theory · Mathematics 2025-11-25 Tuan Pham , Alessandro Rinaldo , Purnamrita Sarkar