CCEN 746 Blockchain Applications, Design, and Systems
This course consists of two parts and discusses the fundamentals of optimization techniques with a focus on engineering applications. In the first part, the main topics are an overview of convex optimization theory and its applications, as well as an introduction to various classical convex optimization problems along with their solutions. The second part deals with the basics of reinforcement learning (RL), primarily focusing on multi-armed bandits, dynamic programming, Monte Carlo, temporal-difference learning, deep Q-networks, and policy gradient algorithms.
Offered
Fall