There is a deep analogy between statistical inference and statistical physics. I will give a friendly introduction to both of these fields. I will then discuss phase transitions in problems like community detection in networks, and clustering of sparse high-dimensional data, where if our data becomes too sparse or too noisy it becomes impossible to find the underlying pattern; moreover, I will discuss optimal algorithms that succeed as well as possible up to this point. Along the way, I will visit ideas from computational complexity, random graphs, random matrices, and spin glass theory.
This lecture is part of Games, Epidemics and Behavior
Lecture 1: 28 June 2016, 4:00 PM (for general scientific audience)
Lecture 2: 29 June 2016, 4:00 PM
Lecture 3: 30 June 2016, 4:00 PM
Venue: Ramanujan Lecture Hall, ICTS, Bangalore