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UID:942@fds.yale.edu
DTSTART;TZID=America/New_York:20260305T113000
DTEND;TZID=America/New_York:20260305T170000
DTSTAMP:20260304T204657Z
URL:https://fds.yale.edu/events/fds-colloquium-lorenzo-orecchia-chicago-he
 at-diffusions-as-regularized-eigenvectors-for-fast-balanced-partitioning/
SUMMARY:FDS Colloquium: Lorenzo Orecchia (Chicago)\, "Heat Diffusions as Re
 gularized Eigenvectors for Fast Balanced Partitioning"
DESCRIPTION:\nAbstract: We give a novel\, simpler spectral algorithm for th
 e problem of approximating the minimum conductance $b$-balanced cut in an 
 undirected weighted graph. Our method is a simple modification of the recu
 rsive eigenvector algorithm\, where eigenvector computations are replaced 
 heat diffusions\, which act as regularized analogues of the eigenvector. F
 inally\, the algorithm outputs a new kind of certificate for the absence o
 f a balanced cut\, which leads to a number of open questions.\n\n\n\nSpeak
 er Bio: Lorenzo Orecchia is an assistant professor in the Department of Co
 mputer Science at the University of Chicago. Lorenzo’s research focuses 
 on the design of efficient algorithms for fundamental computational challe
 nges in machine learning and combinatorial optimization. His approach is b
 ased on combining ideas from continuous and discrete optimization into a s
 ingle framework for algorithm design. Lorenzo obtained his PhD in computer
  science at UC Berkeley under the supervision of Satish Rao in 2011\, and 
 was an applied mathematics instructor at MIT under the supervision of Jon 
 Kelner until 2014. He was a recipient of the 2014 SODA Best Paper award an
 d a co-organizer of the Simons semester “Bridging Continuous and Discret
 e Optimization” in Fall 2017.\n
CATEGORIES:Fellows Events,FDS Events,Colloquium
LOCATION:Yale Institute for Foundations of Data Science Common Area\, Kline
  Tower 13th Floor\, New Haven\, CT\, 06511\, United States
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Kline Tower 13th Floor\, Ne
 w Haven\, CT\, 06511\, United States;X-APPLE-RADIUS=100;X-TITLE=Yale Insti
 tute for Foundations of Data Science Common Area:geo:0,0
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DTSTART:20251102T010000
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