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SUMMARY:Vishesh Jain (Stanford University)
DTSTART:20210301T140000Z
DTEND:20210301T150000Z
DTSTAMP:20260423T035530Z
UID:EPC/40
DESCRIPTION:Title: <a href="https://researchseminars.org/talk/EPC/40/">Tow
 ards the sampling Lovász local lemma</a>\nby Vishesh Jain (Stanford Unive
 rsity) as part of Extremal and probabilistic combinatorics webinar\n\n\nAb
 stract\nFor a constraint satisfaction problem which satisfies the conditio
 n of the Lovász local lemma (LLL)\, the celebrated algorithm of Moser and
  Tardos allows one to efficiently find a satisfying assignment. In the pas
 t few years\, much work has gone into understanding whether one can effici
 ently sample from approximately the uniform distribution on satisfying ass
 ignments\, or approximately count the number of satisfying assignments\, u
 nder LLL-like conditions.\n\nI will discuss recent algorithmic progress on
  this problem\, joint with Huy Tuan Pham (Stanford) and Thuy Duong Vuong (
 Stanford).\n
LOCATION:https://researchseminars.org/talk/EPC/40/
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