In this paper we examine the importance of the choice of metric in path coupling, and its relationship to stopping time analysis. We give strong evidence that stopping time analysis is no more powerful than standard path coupling. In particular, we prove a stronger theorem for path coupling with stopping times, using a metric which allows us to analyse a one-step path coupling. This approach provides insight for the design of better metrics for specific problems. We give illustrative applications to hypergraph independent sets and SAT instances, hypergraph colourings and colourings of bipartite graphs, obtaining improved results for all these problems
Given a strongly stationary Markov chain ( discrete or continuous) and a finite set of stopping rule...
Matching of metric distributions is a fundamental problem in computer science having numerous real l...
An algorithm observes the trajectories of random walks over an unknown graph $G$, starting from the ...
We give a new method for analysing the mixing time of a Markov chain using path coupling with stoppi...
We analyse the mixing time of Markov chains using path coupling with stopping times. We apply this a...
We analyse the mixing time of Markov chains using path coupling with stopping times. We apply this a...
We analyse the mixing time of Markov chains using path coupling with stopping times. We apply this a...
We analyse the mixing time of Markov chains using path coupling with stopping times. We apply this a...
We present a new technique for constructing and analyzing couplings to bound the convergence rate of...
An important property of discrete-time Markov chains with finite state space is the rate of converge...
A new method for analyzing the mixing time of Markov chains is described. This method is an extensio...
Two decision problems related to the computation of stopping sets in Tanner graphs are shown to be N...
Two decision problems related to the computation of stopping sets in Tanner graphs are shown to be N...
Mappings between trees and piece-wise linear functions are well-known and used in combinatorics and ...
An aperiodic and irreducible Markov chain on a finite state space converges to its stationary distri...
Given a strongly stationary Markov chain ( discrete or continuous) and a finite set of stopping rule...
Matching of metric distributions is a fundamental problem in computer science having numerous real l...
An algorithm observes the trajectories of random walks over an unknown graph $G$, starting from the ...
We give a new method for analysing the mixing time of a Markov chain using path coupling with stoppi...
We analyse the mixing time of Markov chains using path coupling with stopping times. We apply this a...
We analyse the mixing time of Markov chains using path coupling with stopping times. We apply this a...
We analyse the mixing time of Markov chains using path coupling with stopping times. We apply this a...
We analyse the mixing time of Markov chains using path coupling with stopping times. We apply this a...
We present a new technique for constructing and analyzing couplings to bound the convergence rate of...
An important property of discrete-time Markov chains with finite state space is the rate of converge...
A new method for analyzing the mixing time of Markov chains is described. This method is an extensio...
Two decision problems related to the computation of stopping sets in Tanner graphs are shown to be N...
Two decision problems related to the computation of stopping sets in Tanner graphs are shown to be N...
Mappings between trees and piece-wise linear functions are well-known and used in combinatorics and ...
An aperiodic and irreducible Markov chain on a finite state space converges to its stationary distri...
Given a strongly stationary Markov chain ( discrete or continuous) and a finite set of stopping rule...
Matching of metric distributions is a fundamental problem in computer science having numerous real l...
An algorithm observes the trajectories of random walks over an unknown graph $G$, starting from the ...