Concentration on HDX: Derandomization Beyond Chernoff - Lecture
Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it Explore a cutting-edge computer science and discrete mathematics seminar on concentration bounds and derandomization techniques. Delve into the evolution of Chernoff's bound, from the Expander-Chernoff Theorem to high-dimensional expanders (HDX). Examine the limitations of expander walks for higher degree functions and discover how HDX offer a solution for achieving stronger concentration results. Investigate the implications of these advancements for agreement testing, probabilistically checkable proofs (PCPs), and reverse hypercontractivity. Learn about the latest research closing the gap between HDX and complete hypergraph concentration bounds, presented by Max Hopkins from the Institute for Advanced Study.