Abstract
We present a new technique for constructing and analyzing couplings to bound the convergence rate of finite Markov chains. Our main theorem is a generalization of the path coupling theorem of Bubley and Dyer, allowing the defining partial couplings to have length determined by a random stopping time. Unlike the original path coupling theorem, our version can produce multistep (non-Markovian) couplings. Using our variable length path coupling theorem, we improve the upper bound on the mixing time of the Glauber dynamics for randomly sampling colorings.
| Original language | English |
|---|---|
| Pages (from-to) | 251-272 |
| Number of pages | 22 |
| Journal | Random Structures and Algorithms |
| Volume | 31 |
| Issue number | 3 |
| DOIs | |
| State | Published - Oct 2007 |
Keywords
- Markov Chain Monte Carlo
- Non-Markovian coupling
- Path coupling
- Random sampling
Fingerprint
Dive into the research topics of 'Variable length path coupling'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver