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A $k$-height on a graph $G=(V, E)$ is an assignment $V\to\{0, \ldots, k\}$ such that the value on ajacent vertices differs by at most $1$. We study the Markov chain on $k$-heights that in each step selects a vertex at random, and, if…

Discrete Mathematics · Computer Science 2024-10-14 Stefan Felsner , Daniel Heldt , Sandro Roch , Peter Winkler

We survey existing techniques to bound the mixing time of Markov chains. The mixing time is related to a geometric parameter called conductance which is a measure of edge-expansion. Bounds on conductance are typically obtained by a…

Data Structures and Algorithms · Computer Science 2016-03-07 Venkatesan Guruswami

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

Perturbation analysis of Markov chains provides bounds on the effect that a change in a Markov transition matrix has on the corresponding stationary distribution. This paper compares and analyzes bounds found in the literature for finite…

Probability · Mathematics 2024-04-03 Karim Abbas , Joost Berkhout , Bernd Heidergott

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

We study the limiting object of a sequence of Markov chains analogous to the limits of graphs, hypergraphs, and other objects which have been studied. Following a suggestion of Aldous, we assign to a sequence of finite Markov chains with…

Logic · Mathematics 2015-03-13 Henry Towsner

For general spin systems, we prove that a contractive coupling for any local Markov chain implies optimal bounds on the mixing time and the modified log-Sobolev constant for a large class of Markov chains including the Glauber dynamics,…

Establishing cutoff, an abrupt transition from "not mixed" to "well mixed", is a classical topic in the theory of mixing times for Markov chains. Interest has grown recently in determining not only the existence of cutoff and the order of…

Probability · Mathematics 2024-12-11 Evita Nestoridi , Sam Olesker-Taylor

We introduce a Markov chain for sampling from the uniform distribution on a Riemannian manifold $\mathcal{M}$, which we call the $\textit{geodesic walk}$. We prove that the mixing time of this walk on any manifold with positive sectional…

Probability · Mathematics 2017-11-28 Oren Mangoubi , Aaron Smith

We derive the first explicit bounds for the spectral gap of a random walk Metropolis algorithm on $R^d$ for any value of the proposal variance, which when scaled appropriately recovers the correct $d^{-1}$ dependence on dimension for…

Probability · Mathematics 2024-09-25 Christophe Andrieu , Anthony Lee , Sam Power , Andi Q. Wang

In the Fastest Mixing Markov Chain problem, we are given a graph $G = (V, E)$ and desire the discrete-time Markov chain with smallest mixing time $\tau$ subject to having equilibrium distribution uniform on $V$ and non-zero transition…

Probability · Mathematics 2024-12-11 Sam Olesker-Taylor , Luca Zanetti

We present a coupling framework to upper bound the total variation mixing time of various Metropolis-adjusted, gradient-based Markov kernels in the `high acceptance regime'. The approach uses a localization argument to boost local mixing of…

Probability · Mathematics 2024-06-24 Nawaf Bou-Rabee , Stefan Oberdörster

Markov chains are one of the well-known tools for modeling and analyzing stochastic systems. At the same time, they are used for constructing random walks that can achieve a given stationary distribution. This paper is concerned with…

Information Theory · Computer Science 2025-01-07 Saber Jafarizadeh

We investigate the mixing rate of a Markov chain where a combination of long distance edges and non-reversibility is introduced: as a first step, we focus here on the following graphs: starting from the cycle graph, we select random nodes…

Probability · Mathematics 2018-02-13 Balázs Gerencsér , Julien Hendrickx

The hitting and mixing times are two fundamental quantities associated with Markov chains. In Peres and Sousi[PS2015] and Oliveira[Oli2012], the authors show that the mixing times and "worst-case" hitting times of reversible Markov chains…

Probability · Mathematics 2019-04-05 Robert M. Anderson , Haosui Duanmu , Aaron Smith

In this paper, we consider the Markov-Chain Monte Carlo (MCMC) approach for random sampling of combinatorial objects. The running time of such an algorithm depends on the total mixing time of the underlying Markov chain and is unknown in…

Discrete Mathematics · Computer Science 2016-09-15 Steffen Rechner , Annabell Berger

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

We analyze the general biased adjacent transposition shuffle process, which is a well-studied Markov chain on the symmetric group $S_n$. In each step, an adjacent pair of elements $i$ and $j$ are chosen, and then $i$ is placed ahead of $j$…

Probability · Mathematics 2025-11-05 Reza Gheissari , Holden Lee , Eric Vigoda

An isoperimetric upper bound on the resistance is given. As a corollary we resolve two problems, regarding mean commute time on finite graphs and resistance on percolation clusters. Further conjectures are presented.

Probability · Mathematics 2012-06-12 Itai Benjamini , Gady Kozma

In this paper, we establish novel concentration inequalities for additive functionals of geometrically ergodic Markov chains similar to Rosenthal inequalities for sums of independent random variables. We pay special attention to the…

Probability · Mathematics 2025-09-26 Alain Durmus , Eric Moulines , Alexey Naumov , Sergey Samsonov , Marina Sheshukova
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