Acceleration by randomization: randomized first order algorithms
for large-scale convex optimization
Abstract: In 1995, Grigoriadis and Khachiyan proposed the very first
sublinear time randomized algorithm for matrix games. In the talk, we
discuss recent explanation, extensions and modifications of this
surprising result and outline their potential applications in large-scale Signal
Processing and Semidefinite Programming.