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UID:www.tcs.tifr.res.in/event/1381
DTSTAMP:20240129T063348Z
SUMMARY:Competing Bandits in Non-Stationary Matching Markets
DESCRIPTION:Speaker: Prof. Avishek Ghosh (Indian Institute of Technology\, 
 Bombay (IITB))\n\nAbstract: \nUnderstanding complex dynamics of two-sided 
 online matching markets\, where the demand-side agents compete to match wi
 th the supply-side (arms)\, has recently received substantial interest. To
  that end\, in this paper\, we introduce the framework of decentralized tw
 o-sided matching market under non stationary (dynamic) environments. We ad
 here to the serial dictatorship setting\, where the demand-side agents hav
 e unknown and different preferences over the supply-side (arms)\, but the 
 arms have fixed and known preference over the agents. We propose and analy
 ze an asynchronous and decentralized learning algorithm\, namely Non-Stati
 onary Competing Bandits (NSCB)\, where the agents play  (restrictive) suc
 cessive elimination type learning algorithms to learn their preference ove
 r the arms. The complexity in understanding such a system stems from the f
 act that the competing bandits choose their actions in an asynchronous fas
 hion\, and the lower ranked agents only get to learn from a set of arms\, 
 not dominated by the higher ranked agents\, which leads to forced explorat
 ion. With carefully defined complexity parameters\, we characterize this f
 orced exploration and obtain sub-linear (logarithmic) regret of NSCB. Furt
 hermore\, we validate our theoretical findings via experiments.\nShort Bio
 :\nAvishek Ghosh (Ph.D UC Berkeley\, 2021) is an Assistant Professor at th
 e department of Systems and Control Engg. and The Centre for Machine Intel
 ligence and Data Science at IIT Bombay. Previously\, he was an HDSI (Data 
 Science) Post-doctoral fellow at the University of California\, San Diego.
  Prior to this\, he completed my PhD from the Electrical Engg. and Compute
 r Sciences (EECS) department of UC Berkeley\, advised by Prof. Kannan Ramc
 handran and Prof. Aditya Guntuboyina. His research interests are broadly i
 n Theoretical Machine Learning\, including Federated Learning and multi-ag
 ent Reinforcement/Bandit Learning. In particular\, Avishek is interested i
 n theoretically understanding challenges in multi-agent systems\, and comp
 etition/collaboration across agents. Before coming to Berkeley\, Avishek c
 ompleted his masters degree from Indian Institute of Science (IISc)\, Bang
 alore (at the Electrical Communication Engg. Dept) and prior Avishek compl
 eted his  bachelors degree from Jadavpur University\, in the dept. of Ele
 ctronics and Telecommunication Engineering.\n
URL:https://www.tcs.tifr.res.in/web/events/1381
DTSTART;TZID=Asia/Kolkata:20240213T160000
DTEND;TZID=Asia/Kolkata:20240213T170000
LOCATION:A-201 (STCS Seminar Room)
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