Add to ORKGWe consider Markovian models on graphs with local dynamics. We show that, under suitable conditions, such Markov chains exhibit both rapid convergence to equilibrium and strong concentration of measure in the stationary distribu-tion. We illustrate our results with applications to some known chains from computer science and statistical mechan-ics
We study the long run behaviour of interactive Markov chains on infinite product spaces. The behavio...
Algorithms based on Markov chains are ubiquitous across scientific disciplines, as they provide a me...
In this paper, we study a notion of local stationarity for discrete time Markov chains which is usef...
We consider Markovian models on graphs with local dynamics. We show that, under suitable conditions,...
This thesis focuses on the rapid mixing of graph-related Markov chains. The main contribution concer...
Graduation date: 2018Markov chains have long been used to sample from probability distributions and ...
A random walk is a basic stochastic process on graphs and a key primitive in the design of distribut...
We study the long run behaviour of interactive Markov chains on in nite product spaces. The behaviou...
Presented as part of the ARC11 lecture on October 30, 2017 at 10:00 a.m. in the Klaus Advanced Compu...
This book is an introduction to the modern approach to the theory of Markov chains. The main goal of...
We study convergence to equilibrium for a class of Markov chains in random environment. The chains a...
Markov Chain Monte Carlo algorithms are often used to sample combinatorial structures such as matchi...
International audienceWe study convergence to equilibrium for a large class of Markov chains in rand...
Random independent sets in graphs arise, for example, in statistical physics, in the hard-core model...
International audienceWe prove concentration inequalities for some classes of Markov chains and Φ-mi...
We study the long run behaviour of interactive Markov chains on infinite product spaces. The behavio...
Algorithms based on Markov chains are ubiquitous across scientific disciplines, as they provide a me...
In this paper, we study a notion of local stationarity for discrete time Markov chains which is usef...
We consider Markovian models on graphs with local dynamics. We show that, under suitable conditions,...
This thesis focuses on the rapid mixing of graph-related Markov chains. The main contribution concer...
Graduation date: 2018Markov chains have long been used to sample from probability distributions and ...
A random walk is a basic stochastic process on graphs and a key primitive in the design of distribut...
We study the long run behaviour of interactive Markov chains on in nite product spaces. The behaviou...
Presented as part of the ARC11 lecture on October 30, 2017 at 10:00 a.m. in the Klaus Advanced Compu...
This book is an introduction to the modern approach to the theory of Markov chains. The main goal of...
We study convergence to equilibrium for a class of Markov chains in random environment. The chains a...
Markov Chain Monte Carlo algorithms are often used to sample combinatorial structures such as matchi...
International audienceWe study convergence to equilibrium for a large class of Markov chains in rand...
Random independent sets in graphs arise, for example, in statistical physics, in the hard-core model...
International audienceWe prove concentration inequalities for some classes of Markov chains and Φ-mi...
We study the long run behaviour of interactive Markov chains on infinite product spaces. The behavio...
Algorithms based on Markov chains are ubiquitous across scientific disciplines, as they provide a me...
In this paper, we study a notion of local stationarity for discrete time Markov chains which is usef...