proximal: videos

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1. 1▶DSCC 435 OPT for ML - 15 Alternating Direction Method of MultipliersOptimization for Machine LearningNotes
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2. 2▶DSCC 435 OPT for ML - 14 Augmented LagrangianOptimization for Machine LearningNotes
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3. 3▶DSCC 435 OPT for ML - 13 Saddle Point ProblemOptimization for Machine LearningNotes
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4. 4▶DSCC 435 OPT for ML - 12 Generalized Inexact Proximal Point FrameworkOptimization for Machine LearningNotes
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5. 5▶DSCC 435 OPT for ML - 11 Inexact Proximal Point FrameworkOptimization for Machine LearningNotes
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6. 6▶DSCC 435 OPT for ML - 4 Gradient MethodOptimization for Machine LearningNotes
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7. 7▶DSCC 435 OPT for ML - 6 Subgradient MethodOptimization for Machine LearningNotes
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8. 8▶DSCC 435 OPT for ML - 3 ComplexityOptimization for Machine LearningNotes
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9. 9▶DSCC 435 OPT for ML - 10 Frank Wolfe MethodOptimization for Machine LearningNotes
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10. 10▶DSCC 435 OPT for ML - 7 Mirror DescentOptimization for Machine LearningNotes
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11. 11▶DSCC 435 OPT for ML - 9 Accelerated Gradient MethodOptimization for Machine LearningNotes
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12. 12▶DSCC 435 OPT for ML - 8 Proximal Gradient MethodOptimization for Machine LearningNotes
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13. 13▶DSCC 435 OPT for ML - 5 Projected Gradient MethodOptimization for Machine LearningNotes
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14. 14▶DSCC 435 OPT for ML - 2 ConvexityOptimization for Machine LearningNotes
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15. 15▶DSCC 435 OPT for ML - 1 IntroductionOptimization for Machine LearningNotes
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16. 16▶Preconditioned Proximal Point Methods | Re-Live of the 27th lectureConvex AnalysisNotes
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17. 17▶The Proximal Point Algorithm | Re-Live of the 26th lectureConvex AnalysisNotes
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18. 18▶Relaxed Mann Iterations | Re-Live of the 25th lectureConvex AnalysisNotes
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19. 19▶Resolvents and non-expansive operators | Re-Live of the 24th lectureConvex AnalysisNotes
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20. 20▶Monotone Operators | Re-Live of the 23rd lectureConvex AnalysisNotes
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21. 21▶Analysis of the Proximal Gradient Method and its Acceleration | Re-Live of the 22nd lectureConvex AnalysisNotes
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22. 22▶Accelerated Gradient Descent | Re-Live of the 21st lectureConvex AnalysisNotes
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23. 23▶Subgradient Method and Gradient Descent | Re-Live of the 20th lectureConvex AnalysisNotes
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24. 24▶More Worst Case Analysis | Re-Live of the 19th lectureConvex AnalysisNotes
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25. 25▶Convergence Rates and Worst Case Analysis | Re-Live of the 18th lectureConvex AnalysisNotes
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26. 26▶Classes of Optimisation Problems | Re-Live of the 17th lectureConvex AnalysisNotes
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27. 27▶Examples of Duality & Optimality Systems | Re-Live of the 16th lectureConvex AnalysisNotes
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28. 28▶Fenchel-Rockafellar Duality | Re-Live of the 15th lectureConvex AnalysisNotes
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29. 29▶Conjugation calculus | Re-Live of the 14th lectureConvex AnalysisNotes
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30. 30▶Convex conjugation | Re-Live of the 13th lectureConvex AnalysisNotes
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