EE364b - Course Information

Spring 2019

Course schedule: Mon, Wed 3:00 PM - 4:20 PM

Location: Herrin T175

Instructor: Mert Pilanci, pilanci@stanford.edu

Instructor Office Hours: Tuesday 2-4pm in Packard 255

TA: Steven Diamond, diamond@cs.stanford.edu

office hours: Thursday 3-5pm, Packard 109

TA: Abbas Kazerouni, abbask@stanford.edu

office hours: Monday 5pm-6:30pm in Packard 107

Units: 3

Grading:

HW 30%, Project/Final 70%

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 project or a final exam.

Prerequisites:

EE364a - Convex Optimization I