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UID:www.tcs.tifr.res.in/event/1060
DTSTAMP:20230921T105045Z
SUMMARY:Battle of Bandits: Online Learning from Relative Preferences
DESCRIPTION:Speaker: Aditya Gopalan (Indian Institute of Science\, Bangalor
 e)\n\nAbstract: \nWe consider the problem of sequentially learning good al
 ternatives from among a pool\, but with only relative utility feedback fro
 m adaptively chosen subsets. At each round\, the learner chooses a subset 
 of alternatives and can observe which ones are preferred over the others i
 n the subset. This type of feedback is natural in several domains\, especi
 ally where human preferences are elicited in a repeated fashion ("Which of
  A\, B\, C\, D do you prefer?")\, e.g.\, the design of surveys and expert 
 reviews\, web search and recommender systems\, and other settings like ran
 king in multiplayer games. Tranditional approaches such as the multi-armed
  bandit model only absolute utility feedback\, and are thus inadequate to 
 express relative choices. The dueling bandit (Yue-Joachims'09) is a more r
 ecent attempt to model online learning with pairwise preferences\, but the
  more general\, realistic\, and combinatorially harder case of working wit
 h preferences expressed over subsets has largely been unexplored. We take 
 a step in this direction and formulate what we call the battling bandit pr
 oblem\, where one seeks to learn an optimal item or ranking of n items by 
 sequentially choosing up to size-k subsets at each round and exploiting re
 lative preferences arising from a choice model such as the well-known Plac
 kett-Luce probability model. We study variants of learning objectives from
  subsetwise feedback: Identifying the best item\, the set of top-k items\,
  full ranking etc.\, in both the probably approximately correct (PAC) or r
 egret optimization setting\, and design algorithms with optimality propert
 ies. This is joint work with Aadirupa Saha (Indian Institute of Science).\
 nBio:\nAditya Gopalan is an Assistant Professor and INSPIRE Faculty Fellow
  at the Indian Institute of Science\, Dept. of Electrical Communication En
 gineering. He received the Ph.D. degree in electrical engineering from The
  University of Texas at Austin\, and the B.Tech. and M.Tech. degrees in el
 ectrical engineering from the Indian Institute of Technology Madras. He wa
 s an Andrew and Erna Viterbi Post-Doctoral Fellow at the Technion-Israel I
 nstitute of Technology. His research interests include machine learning an
 d statistical inference\, control\, and resource allocation algorithms.\n
URL:https://www.tcs.tifr.res.in/web/events/1060
DTSTART;TZID=Asia/Kolkata:20200512T140000
DTEND;TZID=Asia/Kolkata:20200512T150000
LOCATION:A-201 (STCS Seminar Room)
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