EE227A
Convex Optimization -- Spring 2013
EE227A
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Syllabus
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LECTURES
Lecture 1
Lecture 2
Lecture 3
Lecture 4
Lecture 5
Lecture 6
Lecture 7
Lecture 8
Lecture 9
Lecture 10
Lecture 11
Lecture 12
Lecture 13
Lecture 14
Lecture 15
Lecture 16
Lecture 17
Lecture 18
Lecture 19
Lecture 20
Lecture 21
Lecture 22
Lecture 23
Lecture 24
Lecture 25
Lecture 26
Lecture 27
Lecture 28
Lecture slides
Several of the slides have (harmless, easily fixable) typos that my students found, or I noticed while lecturing. I hope to fix these when I get a chance. If you notice something egregious, please email me. Thanks!
1. [22/01] Introduction to optimization
2. [24/01] Convex sets and functions
3. [29/01] Convex sets and functions
4. [31/01] Conjugates, subdifferentials
5. [05/02] Optimization problems
6. [07/02] Conic Optimization
7. [12/02] Cancelled
8. [14/02] Weak duality, sdp example
9. [19/02] Quiz
10. [21/02] Duality, strong duality, saddle points
11. [26/02] Duality, minimax, optimality conditions
12. [28/02] Subgradient methods
13. [05/03] Gradient methods I (basics, unconstrained)
14. [07/03] Gradient methods – II (convergence, constrained problems)
15. [12/03] Gradient methods – III (optimal methods, proximal splitting)
16. [14/03] Review Gradient Projection; Proximal methods; Monotone operators
17. [19/03] Operator splitting; Douglas-Rachford method
18. [21/03] DR, Product space; incremental (proximal) methods I
19. [02/04] Stochastic optimization
20. [04/04] Coordinate descent; Proximal Dykstra
21. [09/04] Randomized BCD, Parallel BCD, Parallel Stochastic Gradient, ADMM
22. [11/04] Parallel, distributed opt - I
23. [16/04] Canceled
24. [18/04] Parallel opt, ADMM, Asynchronous distributed
25. [23/04] Newton, Quasi-Newton, LBFGS, Constrained Newton methods
26. [25/04] Interior point methods (theory only)
27. [30/04] Derivative free optimization (DFO)
28. [02/05] Algebra + Optimization, Polynomials, sums of squares