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SUMMARY:Distributed Adversarial Bandits
DTSTART:20260320T110000
DTEND:20260320T120000
DTSTAMP:20260416T122833Z
UID:2d2588a1f7b554da27e509ba62ce5952a6edb129e5d62436705bd733
CATEGORIES:Conferences - Seminars
DESCRIPTION:Prof. Nicolò Cesa-Bianchi\, Computer Science at Università 
 degli Studi di Milano\, Italy\nAbstract:\nWe study distributed adversarial
  bandits\, where N agents cooperate to minimize the global average loss wh
 ile observing only their own local losses. We show that the minimax regret
  for this problem is expressed as a combination of a term accounting for t
 he communication cost and a term accounting for the bandit feedback cost. 
 Our upper bound\, which significantly improves over the previous best boun
 d\, is based on a novel black-box reduction to bandits with delayed feedba
 ck which can be extended to more general settings\, like distributed linea
 r bandits. In the talk\, we will place this result in the context of the l
 iterature on multi-agent online learning algorithms.\nJoint work with Hao 
 Qiu and Mengxiao Zhang\n\nBiography:\nNicolò Cesa-Bianchi is professor o
 f Computer Science at Università degli Studi di Milano. His main research
  interests are the design and analysis of algorithms for machine learning 
 and sequential decision-making. He is co-author of the monographs "Predict
 ion\, Learning\, and Games" and "Regret Analysis of Stochastic and Nonstoc
 hastic Multi-armed Bandit Problems". He served as President of the Associa
 tion for Computational Learning and co-chaired the program committees of s
 ome of the most important machine learning conferences\, including NeurIPS
  and COLT. He is the recipient of a Google Research Award\, a Xerox Founda
 tion Award\, a Criteo Faculty Award\, a Google Focused Award\, an IBM Rese
 arch Award\, and the FOCS Test-of-Time Award. He is ELLIS fellow\, member 
 of the ELLIS board\, and co-director of the ELLIS program on Interactive L
 earning and Interventional Representations. He is member of the Italian Ac
 ademy of Sciences.
LOCATION:ME C2 405 https://plan.epfl.ch/?room==ME%20C2%20405
STATUS:CONFIRMED
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