| dc.contributor.author | Lau, Lap Chi | |
| dc.date.accessioned | 2018-10-29T20:13:04Z | |
| dc.date.available | 2018-10-29T20:13:04Z | |
| dc.date.issued | 2018-10-15 | |
| dc.identifier.uri | http://hdl.handle.net/1853/60504 | |
| dc.description | Presented on October 15, 2018 at 11:00 a.m. in the Klaus Advanced Computing Building, Room 1116E. | en_US |
| dc.description | Lap 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.description | Runtime: 60:19 minutes | en_US |
| dc.description.abstract | The 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.extent | 60:19 minutes | |
| dc.language.iso | en_US | en_US |
| dc.relation.ispartofseries | ARC Colloquium | en_US |
| dc.subject | Operator scaling | en_US |
| dc.subject | Paulsen problem | en_US |
| dc.subject | Smoothed analysis | en_US |
| dc.title | The Paulsen problem, continuous operator scaling, and smoothed analysis | en_US |
| dc.type | Lecture | en_US |
| dc.type | Video | en_US |
| dc.contributor.corporatename | Georgia Institute of Technology. Algorithms, Randomness and Complexity Center | en_US |
| dc.contributor.corporatename | University of Waterloo. School of Computer Science | en_US |
