EE364b - Course Information

Spring 2021

Course schedule: Tue, Thu 10:30 AM - 11:50 AM live Zoom lectures

Instructor: Mert Pilanci, pilanci@stanford.edu

Instructor Office Hours: see Canvas

TA: Tolga Ergen, ergen@stanford.edu

office hours: see Canvas

Units: 3

Grading:

HW 50%, Project 50%

Course description

Continuation of 364A. Subgradient, cutting-plane, and ellipsoid methods. Decentralized convex optimization via primal and dual decomposition. Monotone operators and proximal methods; alternating direction method of multipliers. Exploiting problem structure in implementation. Convex relaxations of hard problems. Global optimization via branch and bound. Robust and stochastic optimization. Applications in areas such as control, circuit design, signal processing, machine learning and communications. Course requirements include a final project.

Prerequisites:

EE364a - Convex Optimization I