Applications of Algebraic Complexity to Unsupervised Learning

Explore a detailed lecture by Microsoft Research Lab's Principal Researcher Dr. Neeraj Kayal examining the intersection of algebraic complexity theory and unsupervised learning. Delve into the fundamental question of multivariate polynomial computation complexity while discovering proof techniques for demonstrating computational hardness. Learn how these theoretical frameworks translate into practical applications, specifically in developing efficient algorithms for learning arithmetic circuits and unsupervised learning tasks. Benefit from the expertise of a distinguished researcher who has received numerous accolades, including the Godel Prize and Fulkerson Prize for groundbreaking work in primality testing, and whose recent contributions to algebraic complexity theory have earned him the prestigious Infosys Prize and Bhatnagar Award.