Subject to change.
| Date | Topics | Readings |
|---|---|---|
| Tu Jan 29 | Logistics | slides |
| Th Jan 31 | Review | math4ml, linear algebra, convex analysis, optimization, probability |
| Tu Feb 5 | Martingale Inequalities | the reference on wiki page |
| Th Feb 7 | Canceled | Chapter 1 of Foundations of Machine Learning |
| Tu Feb 12 | PAC learning | Chapter 2 of Foundations of Machine Learning |
| Th Feb 14 | Sample complexity for finite H | Chapter 2 of Foundations of Machine Learning |
| Tu Feb 19 | Sample complexity for infinite H | Chapter 3 of Foundations of Machine Learning |
| Th Feb 21 | Sample complexity for infinite H | Chapter 3 of Foundations of Machine Learning |
| Tu Feb 26 | Supervised boosting | Chapter 6 of Foundations of Machine Learning |
| Th Feb 28 | Supervised boosting | Chapter 6 of Foundations of Machine Learning |
| Tu Mar 5 | Generalization in neural networks | Understanding deep learning requires rethinking generalization,Generalization in Deep Learning, A PAC-Bayesian Approach to Spectrally-Normalized Margin Bounds for Neural Networks |
| Th Mar 7 | Generalization in neural networks | continue |
| Tu Mar 12 | Generalization in neural networks | continue |
| Th Mar 14 | Intro to Graphical Models | Bishop's book: Chapter 8,Murphy's Book: Chapter 19 |
| Tu Mar 19 | Spring Break | |
| Th Mar 21 | Spring Break | |
| Tu Mar 26 | Intro to Graphical Models;MLE for Gaussian Mixtures | Guaranteed Learning of Latent Variable Models through Tensor Methods |
| Th Mar 28 | Method of Moments and Tensor Notations | Tensor Review with highlights, Guaranteed Learning of Latent Variable Models through Tensor Methods |
| Tu Apr 2 | Topic Models | Latent Variable Model:Page 2773-2780, Guaranteed Learning of Latent Variable Models through Tensor Methods |
| Th Apr 4 | Tensor Decompositions | Guaranteed Learning of Latent Variable Models through Tensor Methods |
| Tu Apr 9 | Tensor Decomposition | continue |
| Th Apr 11 | Tensor Decomposition | continue |
| Tu Apr 16 | Reinforcement Learning | RL intro |
| Th Apr 18 | Reinforcement Learning | RL dynamic programming and Monte Carlo prediction |
| Tu Apr 23 | Reinforcement Learning | RL Monte Carlo and Temporal Difference (TD) |
| Th Apr 25 | Reinforcement Learning | RL TD and Approximate Solution Methods |
| Tu Apr 30 | Reinforcement Learning | RL Actor-Critic Method |
| Th May 2 | Reinforcement Learning | Deep RL |
| Tu May 7 | Rescheduled for final project presentation | |
| Th May 9 | Rescheduled for final project presentation | |
| Tu May 14 | Last Day of Class | Rescheduled for final project presentation |