Canonical Paths for MCMC: from Art to Science

Article Details
Title:	Canonical Paths for MCMC: from Art to Science
Article URLs:	https://doi.org/10.1137/1.9781611974331.ch38 http://dl.acm.org/citation.cfm?id=2884473
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Authors:	Lingxiao Huang	Tsinghua University, Institute of Interdisciplinary Information Sciences
	Pinyan Lu	Microsoft Research
	Chihao Zhang	Shanghai Jiao Tong University
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DBLP Key:	conf/soda/HuangLZ16
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ACM Symposium on Discrete Algorithms, SODA 2016