Rishabh
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Optimization in Machine Learning Online Class
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Optimization in Machine Learning (Lecture 11): Applications
Optimization in Machine Learning (Lecture 10): Difference of Submodular Opt, SCSC & SCSK
Optimization in Machine Learning (Lecture 9):Submodular Maximization and Greedy
Optimization in Machine Learning (Lecture 8): Polyhedra, Extensions, and Submodular Minimization
Optimization in Machine Learning (Lecture 7 Continued): Submodular Information Measures
Optimization in Machine Learning: Lec 7 (Submodular Functions: Definitions, Examples, Properties)
Optimization in Machine Learning: Lecture 6.2 (SGD for Deep Learning)
Optimization in Machine Learning: Lecture 6.1 (Stochastic Gradient Descent)
Optimization in Machine Learning: Lecture 5 (Second Order Methods and Coordinate Descent)
Optimization in Machine Learning: Lec 4 (Conditional GD and Projected GD, Quasi-Newton, BFGS etc.)
Optimization in Machine Learning: Lec 3 (Gradient Descent Cont., Nesterov's GD, Proximal GD, Demos)
Optimization in Machine Learning: Lecture 2 (Convex Functions Cont, Analysis of Gradient Descent)
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