convex functions

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1. 1▶Parallel Transport of VectorsInformation Geometry and its ApplicationsNotes
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2. 2▶Tangent space, basis vectors, and Riemannian metricInformation Geometry and its ApplicationsNotes
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3. 3▶Affine and dual affine coordinate systemsInformation Geometry and its ApplicationsNotes
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4. 4▶Legendre transform of convex functions and Bregman divergenceInformation Geometry and its ApplicationsNotes
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5. 5▶Convex functions and Bregman divergence: Examples of Bregman divergenceInformation Geometry and its ApplicationsNotes
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6. 6▶Convex functions and Bregman divergence: Bregman divergenceInformation Geometry and its ApplicationsNotes
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7. 7▶Convex functions and Bregman divergence: Convex functionsInformation Geometry and its ApplicationsNotes
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8. 8▶Examples of divergenceInformation Geometry and its ApplicationsNotes
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9. 9▶Divergence between two pointsInformation Geometry and its ApplicationsNotes
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10. 10▶Manifolds of probability distributions: Discrete distributionsInformation Geometry and its ApplicationsNotes
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11. 11▶Manifolds of probability distributions: Gaussian distributionsInformation Geometry and its ApplicationsNotes
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12. 12▶Information geometry and mechanicsInformation Geometry and its ApplicationsNotes
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13. 13▶An overview of information geometryInformation Geometry and its ApplicationsNotes
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14. 14▶Discrete Geometric Mechanics, Information Geometry, Accelerated Optimization and Machine LearningInformation Geometry and its ApplicationsNotes
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15. 15▶Manifolds, charts, and atlasesInformation Geometry and its ApplicationsNotes
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16. 16▶1.1 Introduction to Optimization and to MeOptimization AlgorithmsNotes
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17. 17▶1.2 What these Lectures do and do not coverOptimization AlgorithmsNotes
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18. 18▶3.1 Intro to Gradient and Subgradient DescentOptimization AlgorithmsNotes
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19. 19▶3.4 Convergence RatesOptimization AlgorithmsNotes
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20. 20▶3.3 Properties of Smooth and Strongly Convex FunctionsOptimization AlgorithmsNotes
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21. 21▶1.3 Some First ExamplesOptimization AlgorithmsNotes
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22. 22▶2.5 Optimality Conditions for Convex OptimizationOptimization AlgorithmsNotes
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23. 23▶4.1 Oracle Lower BoundsOptimization AlgorithmsNotes
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24. 24▶3.2 Smooth and Strongly Convex FunctionsOptimization AlgorithmsNotes
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25. 25▶2.6 Optimality Conditions and ProjectionOptimization AlgorithmsNotes
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26. 26▶Mod-01 Lec-01 IntroductionComputer - Numerical OptimizationNotes
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27. 27▶Mod-02 Lec-02 Mathematical BackgroundComputer - Numerical OptimizationNotes
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28. 28▶Mod-02 Lec-03 Mathematical Background (contd)Computer - Numerical OptimizationNotes
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29. 29▶Mod-06 Lec-11 Line Search TechniquesComputer - Numerical OptimizationNotes
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30. 30▶Mod-06 Lec-12 Global Convergence TheoremComputer - Numerical OptimizationNotes
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31. 31▶Mod-03 Lec-05 One Dimensional Optimization (contd)Computer - Numerical OptimizationNotes
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32. 32▶Mod-04 Lec-06 Convex SetsComputer - Numerical OptimizationNotes
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33. 33▶Mod-04 Lec-07 Convex Sets (contd)Computer - Numerical OptimizationNotes
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34. 34▶Mod-05 Lec-08 Convex FunctionsComputer - Numerical OptimizationNotes
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35. 35▶Mod-05 Lec-09 Convex Functions (contd)Computer - Numerical OptimizationNotes
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