References:
Bertsimas, Dimitris, and John N. Tsitsiklis. Introduction to linear optimization.
Boyd, Stephen P., and Lieven Vandenberghe. Convex optimization.
Bubeck, Sébastien. Convex optimization: Algorithms and complexity.
Grading: 40% HW + 30 % Midterm + 30 % Final
Weekly schedule:
Linear programming and Polyhdra. lecture, scribe
Simplex and Duality. lecture, scribe
Linear Duality and Ellipsoid. lecture, scribe
Ellipsoid and Convexity. lecture, scribe
Convex Optimization, MaxCut. lecture, scribe
SDP Relaxation; Lagrangian Duality. lecture, scribe
Lagrangian Duality and KKT. lecture, scribe
Midterm
Newton's method. lecture, scribe
Self-concordance and Convergence of Newton. lecture, scribe
Interior Point Method. lecture, scribe
Gradient Method and Oracle Complexity. lecture, scribe
Gradient Methods with Stochasticity, Nonconvexity and Mirror Maps. lecture, scribe
Mirror Descent and Online Learning. lecture, scribe
Final