Explore the fundamentals of min-max optimization in this lecture from the Learning and Games Boot Camp. Delve into equilibrium computation, adversarial gradient descent, and zero-sum games as Constantinos Daskalakis from MIT guides you through the intersection of classical optimization techniques and deep learning. Gain insights into the applications of these concepts in modern machine learning and game theory, comparing traditional approaches with contemporary deep learning methodologies.
Overview
Syllabus
Introduction
Welcome
Optimization
Equilibrium Computation
Adversarial
Gradient Descent
Summary
ZeroSum Games
Classical vs Deep Learning
Deep Learning
Taught by
Simons Institute
