Lecture 16 | Convex Optimization I (Stanford)

[@shiv093]

0:41 Summary of lecture 15 6:25 Classical convergence analysis 12:57 Self concordance 15:25 Self-concordant functions 17:56 Self-concordant calculus 20:52 Convergence analysis for self-concordant functions 28:06 numerical example 33:58 Implementation 39:39 example of dense Newton system with structure 52:02 Equality constrained minimization 54:04 equality constrained quadratic minimization 57:26 Eliminating equality constraints 59:44 example 1:02:44 Newton step 1:06:19 Newton decrement 1:07:09 Newton's method with equality constraints 1:07:58 Newton's method and elimination 1:10:07 Newton step at infeasible points

[@toddflanagan5531]

Equality constrained minimization is Ch. 10 in my book. 52:00

[@slippinchillin]

This absolutely saved my day, thank you!

[@Thien--Nguyen]

In 2021, it's looking like we're back at trying to avoid Newton's Method at all cost again with a billion variables O.O

[@shupengwei9419]

chapter 11 52:00

[@annawilson3824]

1:03:36

[@tag_of_frank]

Cameraman fell asleep at 1:06:34