We 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 distribution. We illustrate our results with applications to some known chains from computer science and statistical mechanics
In this paper, we study a notion of local stationarity for discrete time Markov chains which is usef...
We study the long run behaviour of interactive Markov chains on infinite product spaces. The behavio...
In this thesis we discuss concentration inequalities, relaxation to equilibrium of stochastic dynami...
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...
This book is an introduction to the modern approach to the theory of Markov chains. The main goal of...
Presented as part of the ARC11 lecture on October 30, 2017 at 10:00 a.m. in the Klaus Advanced Compu...
We study convergence to equilibrium for a class of Markov chains in random environment. The chains a...
International audienceWe prove concentration inequalities for some classes of Markov chains and Φ-mi...
Random independent sets in graphs arise, for example, in statistical physics, in the hard-core model...
International audienceWe study convergence to equilibrium for a large class of Markov chains in rand...
Markov Chain Monte Carlo algorithms are often used to sample combinatorial structures such as matchi...
In this paper, we study a notion of local stationarity for discrete time Markov chains which is usef...
We study the long run behaviour of interactive Markov chains on infinite product spaces. The behavio...
In this thesis we discuss concentration inequalities, relaxation to equilibrium of stochastic dynami...
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...
This book is an introduction to the modern approach to the theory of Markov chains. The main goal of...
Presented as part of the ARC11 lecture on October 30, 2017 at 10:00 a.m. in the Klaus Advanced Compu...
We study convergence to equilibrium for a class of Markov chains in random environment. The chains a...
International audienceWe prove concentration inequalities for some classes of Markov chains and Φ-mi...
Random independent sets in graphs arise, for example, in statistical physics, in the hard-core model...
International audienceWe study convergence to equilibrium for a large class of Markov chains in rand...
Markov Chain Monte Carlo algorithms are often used to sample combinatorial structures such as matchi...
In this paper, we study a notion of local stationarity for discrete time Markov chains which is usef...
We study the long run behaviour of interactive Markov chains on infinite product spaces. The behavio...
In this thesis we discuss concentration inequalities, relaxation to equilibrium of stochastic dynami...
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