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CALSCALE:GREGORIAN
BEGIN:VEVENT
UID:www.tcs.tifr.res.in/event/1783
DTSTAMP:20261016T090242Z
SUMMARY:Fair Clustering and Consensus
DESCRIPTION:Speaker: Diptarka Chakraborty (National University of Singapore
 )\n\nAbstract: \nClustering is a fundamental task in data analysis\, but t
 he resulting clusters may not ensure fair representation of different popu
 lation groups. In this talk\, I will discuss a series of works investigati
 ng how to incorporate fairness into clustering while preserving the qualit
 y of the solution. We first consider the problem ofmodifying an existing c
 lustering to ensure proportional representation of different groups while 
 making minimal changes. We explore the computational challenges of this pr
 oblem and develop efficient approximation algorithms\, extending from two 
 groups to arbitrarily many groups. Building on these results\, we study ho
 w to combine multiple clusterings into a single fair consensus. Finally\, 
 we investigate how to achieve fair consensus efficiently in large-scale se
 ttings where clusterings arrive sequentially\, and memory is limited.\n
URL:https://www.tcs.tifr.res.in/web/events/1783
DTSTART;TZID=Asia/Kolkata:20261210T103000
DTEND;TZID=Asia/Kolkata:20261210T111500
LOCATION:Homi Bhabha Auditorium
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