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