【Abstract】Convex optimization has emerged as useful tool for applications that include data analysis and model fitting, resource allocation, engineering design, network design and optimization, finance, and control and signal processing.This talk will focus on disciplined convex programming (DCP), a simple but powerful method for specifying optimization problems that are convex. We show how CVXPY, an implementation based on DCP,can be used for distributed convex optimization.

【Bio】 Stephen Boyd is the Samsung Professor of Engineering, and Professor of Electrical Engineering in the Information Systems Laboratory at Stanford University, with courtesy appointments in Computer Science and Management Science and Engineering.He received the A.B. degree in Mathematics from Harvard University in 1980, and the Ph.D. in Electrical Engineering and Computer Science from the University of California, Berkeley, in 1985, and then joined the faculty at Stanford.His current research focus is on convex optimization applications in control, signal processing, machine learning, finance, and circuit design.