Lectures

  • 22-Jan: Course overview. Introduction to optimization.

  • 24-Jan: Convex sets and functions.

  • 29-Jan: Convex functions in more detail

  • 31-Jan: Subdifferentials

  • 5-Feb: Convex optimisation problems

  • 7-Feb: Weak duality, conjugates, crossing

  • 12-Feb: Strong duality, minimax games

  • 14-Feb: Optimality conditions

  • 19-Feb: Conic duality, Farkas lemma, etc.

  • 21-Feb: Gradient methods, CG

  • 26-Feb: Conditional gradient method

  • 28-Feb: Subgradient methods

  • 5-Mar: Accelerated gradient, Mirror Descent

  • 7-Mar: Monotone operators, nonexpansivity

  • 12-Mar: Stochastic gradients

  • 14-Mar: Second-order methods, I

  • 19-Mar: Coordinate descent

  • 21-Mar: Duality and dual decomposition

  • 26-Mar: SPRING BREAK

  • 28-Mar: SPRING BREAK

  • 2-Apr: ADMM + distributed ADMM

  • 4-Apr: Other distributed methods

  • 9-Apr: Decision-making under uncertainty

  • 11-Apr: Robust linear programming

  • 16-Apr: Robust convex problems

  • 18-Apr: Chance constraints

  • 23-Apr: Derivative free optimization

  • 25-Apr: Complexity theory of convex opt

  • 30-Apr: Convex algebraic geometry

  • 2-May: Review