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DTSTART:20220313T070000
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DTSTART:20221106T060000
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DTSTART;TZID=America/Toronto:20221202T120000
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URL:https://uwaterloo.ca/combinatorics-and-optimization/events/combinatoria
 l-optimization-reading-group-jacob-skitsko
SUMMARY:Combinatorial Optimization Reading Group - Jacob Skitsko
CLASS:PUBLIC
DESCRIPTION:TITLE: Boosted Sampling\n\nSpeaker:\n Jacob Skitsko\n\nAffiliat
 ion:\n University of Waterloo\n\nLocation:\n MC 6029 or contact Rian Neog
 i for Zoom link\n\nABSTRACT: We will discuss the boosted sampling techniq
 ue introduced by\nGupta et al. which approximates the stochastic version o
 f problems by\nusing nice approximation algorithms for the deterministic v
 ersion of\nthe problem. We will focus on rooted stochastic Steiner trees a
 s an\nexample\, though other problems are covered by this approach (such a
 s\nvertex cover and facility location). The problem is given to us in two\
 nstages: in the first stage we may choose some elements at a cheaper\ncost
 \, and in the second stage our actual requirements are revealed to\nus\, a
 nd we can buy remaining needed elements at a more expensive cost\n(where c
 osts get scaled by some factor in the second stage). We will\nsee that if 
 our problem is sub-additive\, and we have an\nalpha-approximation algorith
 m for the deterministic version of our\nproblem with a beta-strict cost-sh
 aring function then we can get an\n(alpha + beta)-approximation for the st
 ochastic version of our\nproblem. We also discuss related problems\, for e
 xample the (not\nsub-additive!) unrooted stochastic Steiner tree problem.
DTSTAMP:20260419T155042Z
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