Description:This course will recover research results of the Instructor over the years:1) Elegant nonparametric, minimum distance estimation of a density and a regression type function and of their derivatives, with upper and lower rates of convergence; the parameter space is assumed to be either totally bounded or regular. Plug-in upper convergence rates for estimates of a mixing density in R...
Description:High-dimensional statistical learning has become an increasingly important research area. In this course, we will provide theoretical foundations of high-dimensional learning for several widely studied problems with many applications. More specifically, we will review concentration inequalities, VC dimension, metric entropy and statistical implications, consider high-dimensional lin...