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UID:www.tcs.tifr.res.in/event/1512
DTSTAMP:20250102T052021Z
SUMMARY:Algorithmic Decision-Making in the Presence of Biased Data
DESCRIPTION:Speaker: Nisheeth Vishnoi (Yale University\, US)\n\nAbstract: \
 n\nAlgorithms for optimization problems such as selection\, ranking\, and 
 classification typically assume that the inputs are what they are promised
  to be. However\, in several real-world applications of these problems\, t
 he input may contain systematic biases along socially salient attributes a
 ssociated with inputs such as race\, gender\, or political opinion. Such b
 iases can not only lead the outputs of the current algorithms to output su
 b-optimal solutions with respect to true inputs but may also adversely aff
 ect opportunities for individuals in disadvantaged socially salient groups
 . This talk will consider the question of using optimization to solve the 
 aforementioned problems in the presence of biased inputs. It will start wi
 th models of biases in inputs and discuss alternate ways to design algorit
 hms for the underlying problem that can mitigate the effects of biases by 
 taking into account knowledge about biases.\nThis talk is based on several
  joint works with Elisa Celis.\nShort Bio: Nisheeth Vishnoi is the A. Bart
 lett Giamatti Professor of Computer Science at Yale University. His resear
 ch lies at the intersection of computer science\, mathematics\, and societ
 al challenges in an increasingly algorithmic world\, with a focus on the f
 oundations and ethics of artificial intelligence. He is a Fellow of the As
 sociation for Computing Machinery (ACM) and the American Mathematical Soci
 ety (AMS)\, recognized for his contributions to theoretical computer scien
 ce and its connections to mathematics\, sciences\, and social sciences.\n
  \n \n
URL:https://www.tcs.tifr.res.in/web/events/1512
DTSTART;TZID=Asia/Kolkata:20250103T110000
DTEND;TZID=Asia/Kolkata:20250103T120000
LOCATION:A-201 (STCS Seminar Room)
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