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Related papers: Mixing Time Bounds via the Spectral Profile

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We provide new upper bounds for mixing times of general finite Markov chains. We use these bounds to show that the total variation mixing time is robust under rough isometry for bounded degree graphs that are roughly isometric to trees.

Probability · Mathematics 2017-12-06 Louigi Addario-Berry , Matthew I. Roberts

We show that a new probabilistic technique, recently introduced by the first author, yields the sharpest bounds obtained to date on mixing times of Markov chains in terms of isoperimetric properties of the state space (also known as…

Probability · Mathematics 2007-05-23 Ben Morris , Yuval Peres

Mixing of finite time-homogeneous Markov chains is well understood nowadays, with a rich set of techniques to estimate their mixing time. In this paper, we study the mixing time of random walks in dynamic random environments. To that end,…

Probability · Mathematics 2023-09-27 Raphael Erb

We investigate the sharpness of the spectral profile bound presented by Goel et al. and Chen et al. on the $L^{2}$ mixing time of Markov chains on continuous state spaces. We show that the bound provided by Chen et al. is sharp up to a…

Probability · Mathematics 2024-09-18 Elnaz Karimian Sichani , Aaron Smith

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

We introduce a new framework that yields spectral bounds on norms of functions of transition maps for finite, homogeneous Markov chains. The techniques employed work for bounded semigroups, in particular for classical as well as for quantum…

Mathematical Physics · Physics 2015-03-16 Oleg Szehr , David Reeb , Michael M. Wolf

In a series of recent works, Boyd, Diaconis, and their co-authors have introduced a semidefinite programming approach for computing the fastest mixing Markov chain on a graph of allowed transitions, given a target stationary distribution.…

Probability · Mathematics 2011-09-07 S. Roch

We show how to combine Fourier analysis with coupling arguments to bound the mixing times of a variety of Markov chains. The mixing time is the number of steps a Markov chain takes to approach its equilibrium distribution. One application…

Probability · Mathematics 2012-06-19 David Bruce Wilson

We establish the first polynomial upper bound for the mixing time of random edge flips on rooted quadrangulations: we show that the spectral gap of the edge flip Markov chain on quadrangulations with $n$ faces admits, up to constants, an…

Probability · Mathematics 2022-01-13 Alessandra Caraceni , Alexandre Stauffer

Through a Metropolis-like algorithm with single step computational cost of order one, we build a Markov chain that relaxes to the canonical Fermi statistics for k non-interacting particles among m energy levels. Uniformly over the…

Probability · Mathematics 2015-05-14 Alexandre Gaudilliere , Julien Reygner

We prove an upper bound on the total variation mixing time of a finite Markov chain in terms of the absolute spectral gap and the number of elements in the state space. Unlike results requiring reversibility or irreducibility, this bound is…

Probability · Mathematics 2013-10-31 Daniel Jerison

Many finite-state reversible Markov chains can be naturally decomposed into "projection" and "restriction" chains. In this paper we provide bounds on the total variation mixing times of the original chain in terms of the mixing properties…

Probability · Mathematics 2016-02-04 Natesh S. Pillai , Aaron Smith

We prove that Broder's Markov chain for approximate sampling near-perfect and perfect matchings is not rapidly mixing for Hamiltonian, regular, threshold and planar bipartite graphs, filling a gap in the literature. In the second part we…

Discrete Mathematics · Computer Science 2014-04-17 Annabell Berger , Steffen Rechner

We address the problem of estimating the mixing time of a Markov chain from a single trajectory of observations. Unlike most previous works which employed Hilbert space methods to estimate spectral gaps, we opt for an approach based on…

Probability · Mathematics 2023-09-13 Geoffrey Wolfer

We obtain two-sided heat kernel estimates for Riemannian manifolds with ends with mixed boundary condition, provided that the heat kernels for the ends are well understood. These results extend previous results of Grigor'yan and…

Differential Geometry · Mathematics 2025-01-15 Emily Dautenhahn , Laurent Saloff-Coste

We consider a natural local dynamic on the set of all rooted planar maps with $n$ edges that is in some sense analogous to "edge flip" Markov chains, which have been considered before on a variety of combinatorial structures (triangulations…

Probability · Mathematics 2020-01-14 Alessandra Caraceni

Mixing-via-shearing is a powerful and versatile method for establishing mixing properties of smooth parabolic flows. In its quantitative form, it provides upper bounds on the decay of correlations for sufficiently smooth observables.…

Dynamical Systems · Mathematics 2025-12-02 Davide Ravotti

We use a Harnack-type inequality on exit times and spectral bounds to characterize upper bounds of the heat kernel associated with any regular Dirichlet form without killing part, where the scale function may vary with position. We further…

Probability · Mathematics 2025-09-03 Aobo Chen , Zhenyu Yu

Graph spectra have been successfully used to classify network types, compute the similarity between graphs, and determine the number of communities in a network. For large graphs, where an eigen-decomposition is infeasible, iterative moment…

Machine Learning · Statistics 2019-03-27 Diego Granziol , Binxin Ru , Stefan Zohren , Xiaowen Dong , Michael Osborne , Stephen Roberts

We consider unsupervised estimation of mixtures of discrete graphical models, where the class variable corresponding to the mixture components is hidden and each mixture component over the observed variables can have a potentially different…

Machine Learning · Statistics 2012-07-03 A. Anandkumar , D. Hsu , F. Huang , S. M. Kakade
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