Randomized Algorithms for Matrices and Massive Data Sets

Petros Drineas, Michael W. Mahoney

Abstract: The tutorial will cover randomized sampling algorithms that extract structure from very large data sets modeled as matrices or tensors. Both provable algorithmic results and recent work on applying these methods to large biological and internet data sets will be discussed.