| 1 | Overview and Two Open Problems (PDF) |
| 2-4 | Principal Component Analysis in High Dimensions and the Spike Model (PDF) |
| 5-7 | Graphs, Diffusion Maps, and Semi-supervised Learning (PDF) |
| 8-11 | Spectral Clustering and Cheeger's Inequality (PDF) |
| 12-14 | Concentration Inequalities, Scalar and Matrix Versions (PDF) |
| 15-16 | Johnson-Lindenstrauss Lemma and Gordon's Theorem (PDF) |
| 17 |
Local Convergence of Graphs and Enumeration of Spanning Trees (PDF) (Courtesy of Mustazee Rahman. Used with permission.) |
| 18-19 | Compressed Sensing and Sparse Recovery (PDF) |
| 20 | Group Testing and Error-Correcting Codes (PDF) |
| 21 | Approximation Algorithms and Max-Cut (PDF) |
| 22 | Community Detection and the Stochastic Block Model (PDF) |
| 23 | Synchronization Problems and Alignment (PDF) |
