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VERSION:2.0
PRODID:-//Memento EPFL//
BEGIN:VEVENT
SUMMARY:IC Colloquium: Matching in Evolving Environments
DTSTART:20220307T100000
DTEND:20220307T110000
DTSTAMP:20260407T003837Z
UID:cfbae6a6e4cc908a09a74a58a6d71c5d82bb8fcbcb1c862d3cb8b4cb
CATEGORIES:Conferences - Seminars
DESCRIPTION:By: David Wajc - Stanford University\nIC Faculty candidate\n\n
 Abstract\nA pervasive challenge in modern computing is one of uncertainty:
  how should we optimize over continuously-evolving user-generated data\, p
 romptly\, despite uncertainty about future changes to the data? Instantiat
 ions of this question arise in domains as varied as ad serving\, ride hail
 ing and kidney exchanges. Fittingly\, the search for a systematic approach
  to answering such questions has spurred a concerted effort to tackle long
 -standing open problems in the area of decision-making under uncertainty\,
  and to develop generic algorithmic techniques for solving such problems.
  \n\nIn this talk I will present some of my work on algorithms for evolvi
 ng data\, where decisions must be made swiftly (and possibly irrevocably) 
 following changes to their input. In particular\, I will focus on online a
 nd dynamic problems involving matching pairs of people/items\, mirroring t
 he above motivating applications. First\, I will discuss the resolution of
  two decades-old questions in the area of online algorithms\, concerning t
 he online matching and online edge-coloring problems. I will then discuss 
 a general algorithmic framework for the design of dynamic matching algorit
 hms that are robust to adaptively-changing data. Throughout\, I will show 
 how the use of randomization helps solve problems with uncertain input\, a
 nd highlight key techniques used in my work\, most prominently the use of 
 the theory of Negative Association. \n\nBio\nDavid Wajc is the 2020 Motwa
 ni Postdoctoral Fellow in theoretical computer science at Stanford Univers
 ity. He obtained his PhD at Carnegie Mellon University’s Computer Scienc
 e Department\, as part of the interdisciplinary program in Algorithms\, Co
 mbinatorics\, and Optimization. Before coming to CMU\, he obtained his BSc
  and MSc in Computer Science at the Technion\, receiving two excellence in
  teaching awards in the process. His research focuses on the design and an
 alysis of algorithms\, particularly ones dealing with uncertainty about th
 e input\, including online\, dynamic\, streaming and distributed algorithm
 s.\n\nMore information
LOCATION:BC 420 https://plan.epfl.ch/?room==BC%20420 https://epfl.zoom.us/
 j/63160210849?pwd=eVUxUnVoOGZoTXFsc3RtTHRiZ2VDQT09
STATUS:CONFIRMED
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