Seminar at SMU Delhi

July 17, 2013 (Wednesday) , 3:30 PM at Webinar
Speaker: Partha Sarathi Dey, New York Univerity
Title: A new approach to Stein's method for Normal Approximation
Abstract of Talk
Stein's method is a semi-classical tool for establishing distributional convergence with explicit rates, particularly effective in problems involving complex dependencies. Currently there are several approaches for using Stein's method for Gaussian Central Limit theorems, including dependency graphs, exchangeable pairs, zero- and size-biasing. In this talk I will briefly explain the main idea behind the method and describe a new approach for applying the method in proving superdiffusive Central Limit Theorems. The new approach utilizes the fact that each individual summand depends only on a small part of the environment. Our main example will be the number of small subgraphs in ER random graph and number of local maximas in random energy landscapes.