Lecture Schedule

Sep 25 Administrivia and Course Overview. Concentration of Measure. Concentration of Measure Notes
Sep 28 The PAC Model. Notes
Sep 30 VC dimension Notes
Oct 2 No lecture.
Oct 5 No lecture.
Oct 7 VC dimension. The Uniform Convergence Theorem. Notes
Oct 9 Proof of the Uniform Convergence Theorem.
Oct 12 Stochastic Gradient Descent. Draft Notes
Oct 14 SGD contd.
Oct 16 SGD contd.
Oct 19 Spectral Learning. Draft Notes
Oct 21 Spectral Learning contd.
Oct 23 Spectral Learning contd.
Oct 26 Active Learning Draft Notes
Oct 28 Active Learning
Oct 30 Active Learning
Nov 2 Student Presentation: Chicheng Zhang Fourier PCA and Robust Tensor Decomposition: Slides
Nov 4 Student Presentation: Songbai Yan Optimal Learners for Multiclass Problems: Slides
Nov 6 Student Presentation: Yizhen Wang S-squared: An Efficient Algorithm for Graph-based Active Learning: Slides
Nov 9 Student Presentation: Yuchao Liu Spectral Clustering and Block Models: A Review And A New Algorithm: Slides
Nov 11 Veteran's Day. No lecture.
Nov 13 Student Presentation: Joseph Geumlek Distributed Learning, Communication Complexity, and Privacy: Slides
Nov 16 No lecture
Nov 18 Guest Lecturer: Raef Bassily Adaptive Data Analysis
Nov 20 Guest Lecturer: Raef Bassily Adaptive Data Analysis
Nov 23 Student Presentation: Julaiti Alafate A Reliable Effective Tera-Scale Learning System
Nov 25 Student Presentation: Shuang Song Non-negative Matrix Factorization With New Guarantees
Nov 27 No lecture. Thanksgiving!
Nov 30 Student Presentation: Haik Manukian Escaping From Saddle Points --- Online Stochastic Gradient for Tensor Decomposition
Dec 2 Student Presentation: Siyue Wu Random Projection Ensemble Classification
Dec 4 Student Presentation: Sharad Vikram Beating the Perils of Non-Convexity: Guaranteed Training of Neural Networks using Tensor Methods