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dc.contributor.authorLau, Lap Chi
dc.date.accessioned2018-10-29T20:13:04Z
dc.date.available2018-10-29T20:13:04Z
dc.date.issued2018-10-15
dc.identifier.urihttp://hdl.handle.net/1853/60504
dc.descriptionPresented on October 15, 2018 at 11:00 a.m. in the Klaus Advanced Computing Building, Room 1116E.en_US
dc.descriptionLap Chi Lau is an Associate Professor of Computer Science at the University of Waterloo. His research interests are in algorithmic graph theory, approximation algorithms and combinatorial optimization.en_US
dc.descriptionRuntime: 60:19 minutesen_US
dc.description.abstractThe Paulsen problem is a basic open problem in operator theory. We define a continuous version of the operator scaling algorithm to solve this problem. A key step is to show that the continuous operator scaling algorithm converges faster in a perturbed input. To this end, we develop some new techniques in lower bounding the operator capacity, a concept introduced by Gurvits to analyze the operator scaling algorithm. The talk will be self-contained. Joint work with Tsz Chiu Kwok, Yin Tat Lee, and Akshay Ramachandran.en_US
dc.format.extent60:19 minutes
dc.language.isoen_USen_US
dc.relation.ispartofseriesARC Colloquiumen_US
dc.subjectOperator scalingen_US
dc.subjectPaulsen problemen_US
dc.subjectSmoothed analysisen_US
dc.titleThe Paulsen problem, continuous operator scaling, and smoothed analysisen_US
dc.typeLectureen_US
dc.typeVideoen_US
dc.contributor.corporatenameGeorgia Institute of Technology. Algorithms, Randomness and Complexity Centeren_US
dc.contributor.corporatenameUniversity of Waterloo. School of Computer Scienceen_US


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  • ARC Talks and Events [88]
    Distinguished lectures, colloquia, seminars and speakers of interest to the ARC community

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