Schedule

Subject to change.

Date	Topics	Readings	Lecture Slides
Tu Oct 31	Introduction		Course Introduction
Th Sept 2	Math Review		Math Review
Tu Sept 7	Concentration Bound	Concentration Measure	Concentration Bound Part1
Th Sept 9	Concentration Bound cont.		Concentration Bound Part2
Tu Sept 14	Concentration Bound cont. and PAC Learning	Basic tail and concentration bounds	Concentration Bound Part3 and PAC Learning
Tu Sept 16	PAC Learning cont.	Foundation of Machine Learning Chapter 1 Basic tail and concentration bounds	PAC Learning Part2
Tu Sept 21	PAC Learning cont.	Foundation of Machine Learning Chapter 1 Foundation of Machine Learning Chapter 2	PAC Learning Part3
Tu Sept 23	PAC Learning cont.	Foundation of Machine Learning Chapter 2	PAC Learning Part4
Tu Sept 28	VC-Dimension and Boosting	Foundation of Machine Learning Chapter 7	VC-Dim and Boosting
Tu Sept 30	Boosting	Foundation of Machine Learning Chapter 7	Boosting-2
Tu Oct 5	Boosting cont.	Foundation of Machine Learning Chapter 7	Boosting-3
Tu Oct 7	Generalization of Deep Neural Network	Understanding Deep Learning Requires Rethinking Generalization Generalization in Deep Learning	Generalization of DNN
Tu Oct 12	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	Generalization of DNN-2
Tu Oct 14	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
Tu Oct 19	Repelling Evasion and Poisoning Attacks	readings similarly to Oct 14	Repelling Evasion and Poisoning Attacks-2
Thu Oct 21	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-3
Tu Oct 26	Graphical Models	Bishop Chapter 8 Murphy Chapter 19	Graphical Models
Thu Oct 28	Latent Variable Models		Latent Variable Models
Tu Nov 2	Latent Variable Models cont.		Latent Variable Models
Thu Nov 4	Tensor methods		Tensor methods
Tu Nov 9	Tensor methods		Tensor methods
Thu Nov 11	Introduction to Reinforcement Learning		Introduction to RL
Tu Nov 16	Reinforcement Learning - TD methods		RL - TD methods
Thu Nov 18	Reinforcement Learning - Function Apprioximation		RL - Function Apprioximation
Tu Nov 23	Reinforcement Learning - Actor Critic & Intro to Deep Reinforcement Learning		RL-ActorCritic&DRL
Tu Nov 30	Class cancelled
Thu Dec 2	Deep Reinforcement Learning		Deep_RL

Algorithms in Machine Learning: Guarantees and Analyses

Schedule