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The series 'Contraction Methods for Convex Optimization and Monotone Variational Inequalities' contains 20 Lectures.
Part I. Projection and contraction methods for monotone variational inequalities in Lectures 1-5.
Part II. Primal-Dual PPA-Like Methods for convx optimization problems {min f(x) | Ax =b, x in X} in Lectures 6-10.
There are only Chinese Versions for Part I and Part II.
Part III. ADMM for convx optimization problems {min f(x) + g(y) | Ax + By=b, x in X, y in Y}
11. Alternating direction methods of multipliers for separable convex programming
12. Linearized alternating direction methods of multipliers for separable convex programming
13. Alternating direction method of multipliers in sense of customized PPA and its Linearized version
14. Symmetric version of Alternating Direction Method of Multipliers
15. Ergodic and point wise convergence rate of Alternating Direction Method of Multipliers
Part IV. ADMM-Like Methods for convex optimization problems containing more separable blocks
16. Parallel splitting Agumented Lagrangian Method for 3-blocks convex optimization
17. A slightly changed ADMM for convex optimization containing three separable blocks
18. ADMM with Gaussian back substitution for convex optimization containing more separable blocks
19. Partially parallel and regularized ADMM for convex optimization containing more separable blocks
20.VI guided uniform framework of splitting and contraction methods for convex optimization
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