Convex Optimization Stephen Boyd and Lieven Vandenberghe Cambridge University Press More material can be found at the web sites for EE364A (Stanford) or EE236B (UCLA), and our own web pages. Source code for almost all examples and figures in part 2
Prerequisites are linear algebra (preferably abstract) and real analysis (mathematical analysis). Proofs will matter ... but the rich geometry of the subject helps guide the mathematics. Applications: There are many and pervasive ... but do not expe
Convex optimization problems arise frequently in many different fields. A comprehensive introduction to the subject, this book shows in detail how such problems can be solved numerically with great efficiency. The focus is on recognizing convex opti
L. Vandenberghe and S. Boyd SIAM Review, 38(1): 49-95, March 1996. An earlier version, with the name Positive Definite Programming, appeared in Mathematical Programming, State of the Art, J. Birge and K. Murty, editors, pp.276-308, 1994. In semidefi
