Schedule

Subject to change.

Date	Topics	Readings	Lecture Slides	Notes
Wed Jan 25	Introduction		Course Introduction
Mon Jan 30	Math Review		Math Review	Probability Linear Algebra
Wed Feb 1	Concentration Bound	Concentration Measure	Concentration Bound Part1	Concentration Inequality Part1 Typo Correction
Mon Feb 6	Concentration Bound cont.		Concentration Bound Part2	Concentration Inequality Part2
Wed Feb 8	Concentration Bound cont. and PAC Learning	Basic tail and concentration bounds	Concentration Bound Part3
Mon Feb 13	PAC Learning cont.	Foundation of Machine Learning Chapter 1 Basic tail and concentration bounds		Martingales
Wed Feb 15	PAC Learning cont.	Foundation of Machine Learning Chapter 1 Foundation of Machine Learning Chapter 2	Concentration Bound Part4 and PAC Learning Part1
Mon Feb 20	PAC Learning cont.	Foundation of Machine Learning Chapter 2	PAC Learning Part2
Wed Feb 22	VC-Dimension and Boosting	Foundation of Machine Learning Chapter 7	PAC Learning Part3 and VC-Dim Part1
Mon Feb 27	Boosting	Foundation of Machine Learning Chapter 7	VC-Dim Part2
Wed Mar 1	Boosting cont.	Foundation of Machine Learning Chapter 7	Boosting Part1
Mon Mar 6	Midterm Review		Boosting Part2
Wed Mar 8	Midterm Exam
Mon Mar 13	Generalization of Deep Neural Network	Understanding Deep Learning Requires Rethinking Generalization Generalization in Deep Learning	Generalization of DNN
Wed Mar 15	Generalization of Deep Neural Network	Stronger generalization bounds for deep nets via a compression approach Computing Nonvacuous Generalization Bounds for Deep (Stochastic) Neural Networks with Many More Parameters than Training Data
Mon Mar 27	Repelling Evasion and Poisoning Attacks	Poison Frogs! Targeted Clean-Label Poisoning Attacks on Neural Networks Are Adversarial Examples Created Equal? A Learnable Weighted Minimax Risk for Robustness under Non-uniform Attacks ENSEMBLE ADVERSARIAL TRAINING: ATTACKS AND DEFENSES	Repelling Evasion and Poisoning Attacks
Wed Mar 29	Repelling Evasion and Poisoning Attacks	Certified Adversarial Robustness via Randomized Smoothing On the Effectiveness of Interval Bound Propagation for Training Verifiably Robust Models HOW DOES MIXUP HELP WITH ROBUSTNESS AND GENERALIZATION?	Repelling Evasion and Poisoning Attacks-2
Mon Apr 3	Graphical Models	Bishop Chapter 8 Murphy Chapter 19	Graphical Models
Wed Apr 5	Latent Graphical Models
Mon Apr 10	Tensor methods		Tensor methods
Wed Apr 12	Tensor methods
Mon Apr 17	Introduction to Reinforcement Learning		Introduction to RL
Wed Apr 19	Reinforcement Learning - TD methods		RL - TD methods
Mon Apr 24	Reinforcement Learning - TD methods
Wed Apr 26	Reinforcement Learning - Function Apprioximation		RL - Function Apprioximation
Mon May 1	Reinforcement Learning - Actor Critic & Intro to Deep Reinforcement Learning		RL - ActorCritic&DRL
Wed May 3	Deep Reinforcement Learning		Deep RL
Mon May 8
Wed May 10	Final Exam

Algorithms in Machine Learning: Guarantees and Analyses

Schedule