Prerequisites: Mathematical maturity is the main prerequisite. Familiarity with linear algebra, probability, discrete math, and algorithms at the advanced undergraduate level will be assumed.
Meeting time: Tuesdays and Thursdays, 2:30pm-4:00pm
Location: 32-124
Instructors: Costis Daskalakis and Sam Hopkins
Office Hours: By appointment.
Evaluation: Students will be expected to complete two problem sets and a research-oriented course project, which may consist of original research (theoretical and/or experimental!) and/or an exposition of 1 or 2 recent research papers. Tentatively, weight for your final grade will be split as follows: 25% pset 1, 25% pset 2, 50% course project.
| No. | Date | Topics | Notes/References |
|---|---|---|---|
| 1 | Sept. 7 | introduction, uniformity testing on the hypercube | notes part 1, notes part 2 |
| 2 | Sept. 12 | learning high-dimensional gaussians | notes, O’Donnell lecture on Gaussians |
| 3 | Sept. 14 | undirected graphical models | notes |