worst case

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1. 1▶Preconditioned Proximal Point Methods | Re-Live of the 27th lectureConvex AnalysisNotes
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2. 2▶The Proximal Point Algorithm | Re-Live of the 26th lectureConvex AnalysisNotes
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3. 3▶Relaxed Mann Iterations | Re-Live of the 25th lectureConvex AnalysisNotes
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4. 4▶Resolvents and non-expansive operators | Re-Live of the 24th lectureConvex AnalysisNotes
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5. 5▶Monotone Operators | Re-Live of the 23rd lectureConvex AnalysisNotes
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6. 6▶Analysis of the Proximal Gradient Method and its Acceleration | Re-Live of the 22nd lectureConvex AnalysisNotes
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7. 7▶Accelerated Gradient Descent | Re-Live of the 21st lectureConvex AnalysisNotes
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8. 8▶Subgradient Method and Gradient Descent | Re-Live of the 20th lectureConvex AnalysisNotes
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9. 9▶More Worst Case Analysis | Re-Live of the 19th lectureConvex AnalysisNotes
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10. 10▶Convergence Rates and Worst Case Analysis | Re-Live of the 18th lectureConvex AnalysisNotes
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11. 11▶Classes of Optimisation Problems | Re-Live of the 17th lectureConvex AnalysisNotes
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12. 12▶Examples of Duality & Optimality Systems | Re-Live of the 16th lectureConvex AnalysisNotes
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13. 13▶Fenchel-Rockafellar Duality | Re-Live of the 15th lectureConvex AnalysisNotes
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14. 14▶Conjugation calculus | Re-Live of the 14th lectureConvex AnalysisNotes
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15. 15▶Convex conjugation | Re-Live of the 13th lectureConvex AnalysisNotes
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16. 16▶Beyond Worst-Case Analysis (Lecture 15: Smoothed Complexity and Pseudopolynomial-Time Algorithms)Beyond Worst-Case Analysis (Stanford CS264, Fall 2014)Notes
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17. 17▶Beyond Worst-Case Analysis (Lecture 14: Smoothed Analysis of Pareto Curves)Beyond Worst-Case Analysis (Stanford CS264, Fall 2014)Notes
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18. 18▶Beyond Worst-Case Analysis (Lecture 13: Smoothed Analysis of Local Search)Beyond Worst-Case Analysis (Stanford CS264, Fall 2014)Notes
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19. 19▶Beyond Worst-Case Analysis (Lecture 12: LP Decoding/Introduction to Smoothed Analysis)Beyond Worst-Case Analysis (Stanford CS264, Fall 2014)Notes
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20. 20▶Beyond Worst-Case Analysis (Lecture 11: LP Decoding)Beyond Worst-Case Analysis (Stanford CS264, Fall 2014)Notes
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21. 21▶Beyond Worst-Case Analysis (Lecture 10: Planted and Semi-Random Graph Models)Beyond Worst-Case Analysis (Stanford CS264, Fall 2014)Notes
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22. 22▶Beyond Worst-Case Analysis (Lecture 9: A Taste of Compressive Sensing)Beyond Worst-Case Analysis (Stanford CS264, Fall 2014)Notes
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23. 23▶Beyond Worst-Case Analysis (Lecture 8: Exact Recovery in Stable Cut Instances)Beyond Worst-Case Analysis (Stanford CS264, Fall 2014)Notes
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24. 24▶Beyond Worst-Case Analysis (Lecture 7: Perturbation Stability and Single-Link++)Beyond Worst-Case Analysis (Stanford CS264, Fall 2014)Notes
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25. 25▶Beyond Worst-Case Analysis (Lecture 6: Clustering in Approximation-Stable Instances)Beyond Worst-Case Analysis (Stanford CS264, Fall 2014)Notes
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26. 26▶Beyond Worst-Case Analysis (Lecture 5: Computing Independent Sets:A Parameterized Analysis)Beyond Worst-Case Analysis (Stanford CS264, Fall 2014)Notes
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27. 27▶Beyond Worst-Case Analysis (Lecture 4: Parameterized Analysis of Online Paging)Beyond Worst-Case Analysis (Stanford CS264, Fall 2014)Notes
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28. 28▶Beyond Worst-Case Analysis (Lecture 3: Online Paging and Resource Augmentation)Beyond Worst-Case Analysis (Stanford CS264, Fall 2014)Notes
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29. 29▶Beyond Worst-Case Analysis (Lecture 2: Instance-Optimal Geometric Algorithms)Beyond Worst-Case Analysis (Stanford CS264, Fall 2014)Notes
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30. 30▶Beyond Worst-Case Analysis (Lecture 1: Three Motivating Examples)Beyond Worst-Case Analysis (Stanford CS264, Fall 2014)Notes
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