Calendar
Week 1 Introduction and Review
- Jan 9, Jan 11
Week 2 Ensemble Learning
- Jan 16, Jan 18
- LectureEnsemble Learning
- Slides
Week 3 Learning Theory
- Jan 23, Jan 25
Week 4 Advanced Applications
- Jan 30, Feb 1
Happy New Year :)
Course ProjectProject Guideline
Week 5 Spectral Clustering and Semi-Supervised Learning
- Feb 27, Feb 29
- LectureSpectral Clustering and Semi-Supervised Learning Part I
Additional ReadingsBy Akshay Krishnamurthy at UMass
Week 6 Graph Neural Networks
- Mar 5, Mar 7
- LectureGraph Neural Networks
- Slides
Week 7 Nonlinear Dimensionality Reduction and Data Visualization
- Mar 12, Mar 14
Lecture on Mar 14Video (Passcode: t3%&s9G$)
Additional ReadingsBy Cosma Shalizi at CMU
Week 8 Generative Models
- Mar 19, Mar 21
- LectureGenerative Models
- Slides
Assignment 02Assignment
Project Proposal Submission
Week 9 Causal Machine Learning
- Mar 26, Mar 28
Week 10 Privacy in Machine Learning
- Apr 2, Apr 7
Apr 5: Public Holiday Apr 7: Make-up class on Sun
Week 11 Fairness in Machine Learning
- Apr 9, Apr 11
Week 12 Interpretability and Explainability
- Apr 16, Apr 18
Useful Reading and Textbooks: Interpretable Machine Learning by Christoph Molnar
Assignment 03Assignment
Week 13 Course Project Presentation
- Apr 23, Apr 25
Week 14 Course Review Q&A
- Apr 30