Math 49S.02: The Emerging Science of Complex Data
Time: TH, 2:50PM-4:05PM
Location: Physics 205
Instructor: Paul Bendich
Office Hours: Physics 210, TBA
Textbooks: There will be many handouts and other xeroxed readings througout the course of the semester.
Assignments: In addition to regularly assigned response writings and problem sets, there will be a substantial research paper, which
will be accompanied by several benchmark assignments over the course of the semester.
| Date | Topics | Readings | Assignments |
|---|---|---|---|
| Jan. 12 | Overview, Introduction, Motivating Examples | | |
| Jan. 17 | Statistical Learning Theory: Intro | SLT: 1 | |
| Jan. 19 | Basic Probability | SLT: 2-3 | |
| Jan. 24 | Big Data | | |
| Jan. 26 | Noisy Data | | |
| Jan. 31 | Bayesian Analysis | SLT: 4-5 | |
| Feb. 2 | Learning from Examples | SLT: 6 | |
| Feb. 7 | NN and Kernel Rules | SLT: 7-8 | |
| Feb. 9 | Policy Issues: data access, collaboration | | |
| Feb. 14 | Dimension Reduction: Overview | | |
| Feb. 16 | Dimension Reduction: Overview | | |
| Feb. 21 | Multi-dimensional Scaling | | |
| Feb. 23 | IsoMap | | |
| Feb. 28 | Research Project Brainstorming Session | | |
| Mar. 1 | Linear Algebra: vectors, bases, subspaces | | |
| Mar. 13 | Linear Algebra: transformations, eigenvectors | ||
| Mar. 15 | Annotated Bibliographies: Class Discussion | | |
| Mar. 20 | Principal Component Analysis: theory | | |
| Mar. 22 | Principal Component Analysis: examples | | |
| Mar. 27 | Random Walks | | |
| Mar. 29 | Diffusion Maps: Theory | | |
| Apr. 3 | Diffusion Maps: Examples | |
|
| Apr. 5 | Periodicity in Data: Overview | | |
| Apr. 10 | Computational Topology | | |
| Apr. 12 | Topological Data Analysis | | |
| Apr. 17 | Student Presentations | | |
| Apr. 19 | Student Presentations | | |
| Apr. 24 | Student Presentations | | |