Optimization in Machine Learning (Lecture 11): ApplicationsApr 16, 2021 · Rishabh▶Play+Watch later+Read later
Optimization in Machine Learning (Lecture 10): Difference of Submodular Opt, SCSC & SCSKApr 11, 2021 · Rishabh▶Play+Watch later+Read later
Optimization in Machine Learning (Lecture 9):Submodular Maximization and GreedyApr 11, 2021 · Rishabh▶Play+Watch later+Read later
Optimization in Machine Learning (Lecture 8): Polyhedra, Extensions, and Submodular MinimizationApr 2, 2021 · Rishabh▶Play+Watch later+Read later
Optimization in Machine Learning (Lecture 7 Continued): Submodular Information MeasuresMar 27, 2021 · Rishabh▶Play+Watch later+Read later
Optimization in Machine Learning: Lec 7 (Submodular Functions: Definitions, Examples, Properties)Mar 16, 2021 · Rishabh▶Play+Watch later+Read later
Optimization in Machine Learning: Lecture 6.2 (SGD for Deep Learning)Mar 6, 2021 · Rishabh▶Play+Watch later+Read later
Optimization in Machine Learning: Lecture 6.1 (Stochastic Gradient Descent)Mar 6, 2021 · Rishabh▶Play+Watch later+Read later
Optimization in Machine Learning: Lecture 5 (Second Order Methods and Coordinate Descent)Feb 28, 2021 · Rishabh▶Play+Watch later+Read later
Optimization in Machine Learning: Lec 4 (Conditional GD and Projected GD, Quasi-Newton, BFGS etc.)Feb 14, 2021 · Rishabh▶Play+Watch later+Read later
Optimization in Machine Learning: Lec 3 (Gradient Descent Cont., Nesterov's GD, Proximal GD, Demos)Feb 6, 2021 · Rishabh▶Play+Watch later+Read later
Optimization in Machine Learning: Lecture 2 (Convex Functions Cont, Analysis of Gradient Descent)Feb 2, 2021 · Rishabh▶Play+Watch later+Read later
Optimization in Machine Learning: Lecture 1 (Outline, Logistics, Convexity)Jan 23, 2021 · Rishabh▶Play+Watch later+Read later
