| Slides, recordings, and readings for each lecture will be posted on this page as the course progresses. | ||||
| Date | Topic | Slides | Recordings | Readings |
|---|---|---|---|---|
| 1/18 | Course introduction; Fair allocation I: divisible goods | intro, slides | recording | CSC Ch 11, 13 |
| 1/25 | Fair allocation I: indivisible goods | slides | recording | CSC Ch 12 |
| 2/1,2/8 | Proportional Representation in Voting | slides | recording 1 recording 2 |
Ch 2,4 of this book (free PDF available) this tool to play around this tutorial Method of Equal Shares |
| 2/15 | Fair Matching | slides | recording | CSC Ch 14, paper |
| 2/29 | Bias in Machine Learning | slides | recording | paper 1, paper 2 |
| 3/7 | Fair Classification | slides | recording | this tutorial, play around with fairness here and here, impossibility paper 1, impossibility paper 2 |
| 3/14 | Fair Representation Learning Guest Lecturer: Elliot Creager |
slides | No recording | fair representation, multicalibration, adversarially reweighted learning, flexibly fair representation learning, dynamic fairness, robust ML |
| 3/21 | Fair Clustering Guest Lecturer: Evi Micha |
slides | recording | core in clustering, JR in clustering, IF in clustering, balancedness in clustering |
| 4/4 | Project Presentations | — | — | — |
