Phase Transitions in Semidefinite Relaxations (Berkeley-Stanford Colloquium at Berkeley)

Phase Transitions in Semidefinite Relaxations (Berkeley-Stanford Colloquium at Berkeley)

Neyman Seminar
Apr 5, 2016, 04:00 PM - 05:00 PM | 60 Evans Hall | Happening As Scheduled
Andrea Montanari, Stanford University
Statistical inference problems arising within signal processing, data mining, and machine learning naturally give rise to hard combinatorial optimization problems. These problems become intractable when the dimensionality of the data is large, as is often the case for modern datasets. A popular idea is to construct convex relaxations of these combinatorial problems, which can be solved...