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We study the mixing time of the single-site update Markov chain, known as the Glauber dynamics, for generating a random independent set of a tree. Our focus is obtaining optimal convergence results for arbitrary trees. We consider the more…

Discrete Mathematics · Computer Science 2025-03-05 Charilaos Efthymiou , Thomas P. Hayes , Daniel Stefankovic , Eric Vigoda

We obtain moment and Gaussian bounds for general Lipschitz functions evaluated along the sample path of a Markov chain. We treat Markov chains on general (possibly unbounded) state spaces via a coupling method. If the first moment of the…

Probability · Mathematics 2010-12-08 J. -R. Chazottes , F. Redig

We present a new and simple approach to concentration inequalities for functions around their expectation with respect to non-product measures, i.e., for dependent random variables. Our method is based on coupling ideas and does not use…

Probability · Mathematics 2007-05-23 J. -R. Chazottes , P. Collet , C. Kuelske , F. Redig

We give tight concentration bounds for mixtures of martingales that are simultaneously uniform over (a) mixture distributions, in a PAC-Bayes sense; and (b) all finite times. These bounds are proved in terms of the martingale variance,…

Machine Learning · Computer Science 2015-06-23 Akshay Balsubramani

We focus on the log-Sobolev inequality for spin systems on the lattice with interactions of higher order than quadratic. We show that if the one-dimensional single-site measure with boundaries satisfies the log-Sobolev inequality uniformly…

Functional Analysis · Mathematics 2020-01-24 James Inglis , Ioannis Papageorgiou

This paper considers how to obtain MCMC quantitative convergence bounds which can be translated into tight complexity bounds in high-dimensional {settings}. We propose a modified drift-and-minorization approach, which establishes…

Computation · Statistics 2022-05-12 Jun Yang , Jeffrey S. Rosenthal

The maximum a-posteriori (MAP) perturbation framework has emerged as a useful approach for inference and learning in high dimensional complex models. By maximizing a randomly perturbed potential function, MAP perturbations generate unbiased…

Machine Learning · Computer Science 2013-10-17 Francesco Orabona , Tamir Hazan , Anand D. Sarwate , Tommi Jaakkola

We explore some properties of the conditional distribution of an i.i.d. sample under large exceedances of its sum. Thresholds for the asymptotic independance of the summands are observed, in contrast with the classical case when the…

Statistics Theory · Mathematics 2016-10-14 Maeva Biret , Michel Broniatowski , Zangsheng Cao

We study time-inhomogeneous Markov chains to obtain quantitative results on their asymptotic behavior. We use Poincar\'e, Nash, and logarithmic-Sobolev inequalities. We assume that our Markov chain admits a finite invariant measure at each…

Probability · Mathematics 2024-06-25 Nordine Moumeni

This note, mostly expository, is devoted to Poincar{\'e} and log-Sobolev inequalities for a class of Boltzmann-Gibbs measures with singular interaction. Such measures allow to model one-dimensional particles with confinement and singular…

Probability · Mathematics 2020-09-02 Djalil Chafai , Joseph Lehec

We study a problem with three equivalent formulations: describing Gibbs measures for five-vertex model in quadrant; classifying coherent systems on a p-deformation of the Gelfand-Tsetlin graph related to Grothendieck polynomials; finding…

Probability · Mathematics 2026-01-06 Vadim Gorin , Sergei Korotkikh

Gibbs sampling repeatedly samples from the conditional distribution of one variable, x_i, given other variables, either choosing i randomly, or updating sequentially using some systematic or random order. When x_i is discrete, a Gibbs…

Computation · Statistics 2024-03-28 Radford M. Neal

We consider an Ising model on the Cayley tree $\Gamma_k$ of arbitrary order $k\ge1$ with three spin species of values $(\tfrac12,1,\tfrac32)$ distributed deterministically with period three along the generations. Within the framework of…

Probability · Mathematics 2026-02-16 Farrukh Mukhamedov , Muzaffar Rahmatullaev , Obid Karshiboev

There are many research works devoted to Gibbs measure for models on Cayley trees. Among these works, there are some works in which the general results are identical, but the considered models are various. In this article, we present the…

Probability · Mathematics 2023-07-28 F. H. Haydarov

We present a simple algorithm that perfectly samples configurations from the unique Gibbs measure of a spin system on a potentially infinite graph $G$. The sampling algorithm assumes strong spatial mixing together with subexponential growth…

Data Structures and Algorithms · Computer Science 2021-07-01 Konrad Anand , Mark Jerrum

We consider a generic class of log-concave, possibly random, (Gibbs) measures. We prove the concentration of an infinite family of order parameters called multioverlaps. Because they completely parametrise the quenched Gibbs measure of the…

Probability · Mathematics 2022-12-22 Jean Barbier , Dmitry Panchenko , Manuel Sáenz

The aim of this article is to establish asymptotic distributions and consistency of subsampling for spectral density and for magnitude of coherence for non-stationary, almost periodically correlated time series. We show the asymptotic…

Statistics Theory · Mathematics 2011-02-11 Łukasz Lenart

In this paper, we study a class of multilinear Gibbs measures with Hamiltonian given by a generalized $\mathrm{U}$-statistic and with a general base measure. Expressing the asymptotic free energy as an optimization problem over a space of…

Probability · Mathematics 2026-03-31 Sohom Bhattacharya , Nabarun Deb , Sumit Mukherjee

Consider a sequence of Gibbsian line ensembles, whose lowest labeled curves (i.e., the edge) have tight one-point marginals. Then, given certain technical assumptions on the nature of the Gibbs property and underlying random walk measure,…

Probability · Mathematics 2022-01-26 Guillaume Barraquand , Ivan Corwin , Evgeni Dimitrov

This paper is devoted to the study of the generalized impedance boundary conditions (GIBCs) for a strongly absorbing obstacle in the {\bf time} regime in two and three dimensions. The GIBCs in the time domain are heuristically derived from…

Analysis of PDEs · Mathematics 2014-04-23 Hoai-Minh Nguyen , Linh V. Nguyen
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