This is the tentative lecture schedule, with links to scribe notes.
| Lecture 1 (26 Sep) | Introduction. Property testing problem formulation. |
| Lecture 2 (1 Oct) | Concentration inequalities |
| Lecture 3 (3 Oct) | Concentration inequalities + Median of Means |
| Lecture 4 (8 Oct) | List monotonicity in Hamming and l1 distance |
| Lecture 5 (10 Oct) | Bounded degree graph -- connectedness + estimating # connected components |
| Lecture 6 (15 Oct) | More on bounded degree graphs, biclique testing in dense graphs |
| Lecture 7 (17 Oct) | PCP Theorem statement, Connections to (in)approximability |
| Lecture 8 (22 Oct) | Johnson-Lindenstrauss Lemma + Statement of Kirszbraun's extension theorem |
| Lecture 9 (24 Oct) | Distinguishing (discrete) distributions, Various statistical distances |
| Lecture 10 (29 Oct) | Learning a discrete distribution in linear samples, upper and lower bound |
| Lecture 11 (31 Oct) | Uniformity testing + Lower bound of Omega(sqrt(n)) |
| Lecture 12 (5 Nov) | Identity testing -- chi^2-tester, upper bound via Poissonization. Related closeness testers |
| Lecture 13 (7 Nov) | Instance optimal testing, Tolerant testing and relations with estimating parameters, Robust statistics |
| Lecture 14 (12 Nov) | Streaming algorithms setup. Reservoir sampling. Majority element. |
| Lecture 15 (14 Nov) | Count-Distinct Problem -- Deterministic exact lower bound + Algorithm |
| Lecture 16 (19 Nov) | k-wise independence hashing |
| Lecture 17 (21 Nov) | Count-Min sketch |
| Lecture 18 (26 Nov) | Frequency moments |
| No lecture (28 Nov) | Thanksgiving break |
| Lecture 19 (3 Dec) | Optimal 1-d mean estimation |
| Lecture 20 (5 Dec) | Miscellaneous topics/discussions |
Scribing is an important part of learning in this course, and constitutes 20% of the course grade. Students should submit the first draft of their scribe notes no later than 2 days after the corresponding lecture.
Submitted scribe notes should (ideally) be typeset using this LaTeX template.