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DTSTART:20200329T030000
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DTSTART:20191027T020000
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DTSTAMP:20260404T020020Z
UID:5e09fab260e9e057615368@ist.ac.at
DTSTART:20200226T090000
DTEND:20200226T100000
DESCRIPTION:Speaker: Alp Yurtsever\nhosted by Marco Mondelli\nAbstract: Sem
 idefinite programming is a powerful framework from convex optimization tha
 t has striking potential for data science applications. Even so\, practiti
 oners often critique this approach by asserting that it is impossible to s
 olve semidefinite programs at the scale demanded by real-world application
 s. In general\, storage and arithmetic costs prevent us from solving many 
 large-scale optimization problems. As a result\, there is a recent trend w
 here heuristics with unverifiable assumptions are overtaking more rigorous
 \, conventional optimization techniques at the expense of robustness. My r
 ecent research results show that we can overturn this trend by exploiting 
 randomization\, dimensionality reduction and adaptivity at the core of opt
 imization. In this talk\, we would like to argue that the classical convex
  optimization did not reach yet its limits of scalability\, and present a 
 new optimization algorithm that can solve very large semidefinite programm
 ing instances to moderate accuracy using limited arithmetic and minimal st
 orage.
LOCATION:Mondi Seminar Room 2\, Central Building\, ISTA
ORGANIZER:tguggenb@ist.ac.at
SUMMARY:Alp Yurtsever: Scalable Convex Optimization with Applications to Se
 midefinite Programming
URL:https://talks-calendar.ista.ac.at/events/2626
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