Entry Date:
January 29, 2018

High-Dimensional Statistics

Principal Investigator Alexander Rakhlin


This setting is centered around the problem of recovery of high-dimensional and structured signals hidden in noise. Since standard statistical methods are often computationally intractable, the question of interplay between computation and statistical optimality arises. Examples: estimation of communities in networks, recovery of few relevant genes in a large set of gene expression data, etc.