An upper bound on the smallest singular value of a square random matrix

Analysis Seminar
Wednesday, April 11, 2018 - 13:55
1 hour (actually 50 minutes)
Skiles 005
University of Alberta
Consider an n by n square matrix with i.i.d. zero mean unit variance entries. Rudelson and Vershynin showed that its smallest singular value is bounded from above by 1/sqrt{n} with high probability, under the assumption of the bounded fourth moment of the entries. We remove the assumption of the bounded fourth moment, thereby extending the result of Rudelson and Vershynin to a wide range of distributions.