Rating is available when the video has been rented.
This feature is not available right now. Please try again later.
Published on Jul 3, 2016
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