BIOSTAT M280 tentative schedule and handouts (expect frequent updates)
Readings:
| Week | Monday | Wednesday | Homework |
|---|---|---|---|
| 1 | 4/2 introduction and course logistics [slides: ipynb, html] | 4/4 computer languages, Julia intro. [slides: ipynb, html] | |
| 2 | 4/9 Julia programming | 4/11 reproducible research [slides: ipynb, html] | HW1: ipynb, html |
| 3 | 4/16 computer arithmetic [slides: ipynb, html] | 4/18 algo. intro. [slides: ipynb, html] | |
| 4 | 4/23 BLAS [slides: ipynb, html] | 4/25 triangular systems [slides: ipynb, html] | HW2: ipynb, html, nnmf-2429-by-361-face.txt, V0.txt, W0.txt |
| 5 | 4/30 GE/LU [slides: ipynb, html], Cholesky [slides: ipynb, html] | 5/2 QR (GS, Householder, Givens) [slides: ipynb, html] | |
| 6 | 5/7 Sweep operator [slides: ipynb, html], summary of linear regression [slides: ipynb, html], condition number [slides: ipynb, html] | 5/9 iterative methods intro [slides: ipynb, html], easy linear systems [slides: ipynb, html] | HW3: ipynb, html, ucla.zip |
| 7 | 5/14 eigen-decomposition and SVD [slides: ipynb, html], optimization intro. [slides: ipynb, html] | 5/16 Newton-Raphson, Fisher scoring, GLM, nonlinear regression (Gauss-Newton) [slides: ipynb, html] | |
| 8 | 5/21 MM algorithm [Book chapter: pdf] | 5/23 MM algorithm [Slides: pdf] | HW4: ipynb, html, optdigits.tra, optdigits.tes |
| 9 | 5/28 Memorial Day, no class | 5/30 EM algorithm [slides: ipynb, html] | |
| 10 | 6/4 quasi-Newton [slides: ipynb, html], CG and PCG [slides: ipynb, html] | 6/6 convex optimization [slides: ipynb, html], concluding remarks [slides: ipynb, html] | HW5: ipynb, html |