Stephen Wright: Fundamentals of Optimization in Signal Processing

Stephen Wright: Fundamentals of Optimization in Signal Processing

Hausdorff Center for Mathematics via YouTube Direct link

Three Scenarios

2 of 17

2 of 17

Three Scenarios

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Classroom Contents

Stephen Wright: Fundamentals of Optimization in Signal Processing

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  1. 1 Group Sparsity
  2. 2 Three Scenarios
  3. 3 Non-overlapping Groups
  4. 4 Tree-Structured Groups
  5. 5 Matrix Inference Problems
  6. 6 Nuclear Norm Regularization
  7. 7 Another Matrix Inference Problem: Inverse Covariance
  8. 8 Atomic-Norm Regularization
  9. 9 References
  10. 10 Steepest Descent
  11. 11 Backtracking
  12. 12 Weakly convex: 1/k sublinear rate
  13. 13 Linear convergence without strong convexity
  14. 14 The slow linear rate is typical!
  15. 15 Multistep Methods: The Heavy-Ball
  16. 16 Conjugate Gradient
  17. 17 Accelerated First-Order Methods

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