Free Probability, Sample Covariance Matrices and Stochastic Eigen-Inference
Author(s)
Edelman, Alan
Rao, N. Raj
Date Issued
January 2006
Series/Report no.
Computer Science (CS)
Abstract
Random matrix theory is now a big subject with applications in many disciplines of science, engineering and finance. This talk is a survey specifically oriented towards the needs and interests of a computationally inclined audience. We include the important mathematics (free probability) that permit the characterization of a large class of random matrices. We discuss how computational software is transforming this theory into practice by highlighting its use in the context of a stochastic eigen-inference application.
Subjects
Free probability
random matrices
stochastic eigen-inference
rank estimation
principal component analysis
Persistent DSpace Link
