Syllabus

Week Topic Reading Slides Notes Recording
Week 1 Introduction [Slides]
Week 2 Statistical Foundation: Linear Regression, Ridge, and Lasso Section 3.1-3.2 of The Elements of Statistical Learning
Sparsity, the Lasso, and Friends.
Week 3 Statistical Foundation: Lasso, Variable Selection Consistenty, Heterogeneity
Week 4 Statistical Foundation: Ridge, Data Augmentation, Heteroscedasticity
Week 5 Robustness: Domain Adaptation
Week 6 Robustness: Domain Generalization
Week 7 Robustness: Spurious Features
Week 8 Robustness: Adversarial Robustness
Week 9 Spring Break
Week 10 Fairness: Outcome Discrimination
Week 11 Fairness: Quality Disparity
Week 12 Fairness: Applications in Healthcare
Week 13 Privacy Perservation and Federated Learning
Week 14 Interpretability
Week 15 Project Presentation
Week 16 Project Presentation

Instructors

Instructor

Haohan Wang

Research Interests: Trustworthy Machine Learning, Computational Biology

Office Hours: 2-3pm Thursday

Teaching Assistant

Haoyang Liu

Research Interests: dataset distillation, robustness in vision, AI for biomedical research

Office Hours: TBD

Logistics

Please refer to the Canvas page for logistics such as homework and grading.

Projects

Stellar projects at the end of the semester will be displayed here.