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VERSION:2.0
PRODID:-//Memento EPFL//
BEGIN:VEVENT
SUMMARY:Collaborative Estimation
DTSTART:20230807T100000
DTEND:20230807T120000
DTSTAMP:20260410T174215Z
UID:f93c4a7fc32a63d512542fc0cee2347c9be3f022cd23291e3ec7a450
CATEGORIES:Conferences - Seminars
DESCRIPTION:Yunzhen Yao\nEDIC candidacy exam\nExam president: Prof. Emre T
 elatar\nThesis advisor: Prof. Michael Gastpar\nCo-examiner: Prof. Michael 
 Kapralov\n\nAbstract\ncoming soon\n\nBackground papers\n1. Optimal Algorit
 hms for Testing Closeness of Discrete Distributions. Chan\, Diakonikolas\,
  Valiant\, and Valiant\, SODA 2014 (https://arxiv.org/abs/1308.3946).\n2. 
 Which Distribution Distances are Sublinearly Testable? Daskalakis\, Kamath
 \, and Wright\, SODA 2018 (https://arxiv.org/abs/1708.00002).\n3. Alpha-NM
 L Universal Predictors.  Bondaschi and Gastpar\, ISIT 2022 (https://arxiv
 .org/abs/2202.12737v2)
LOCATION:BC 129 https://plan.epfl.ch/?room==BC%20129
STATUS:CONFIRMED
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