Biostat 257
Course Schedule
BIOSTAT 257 tentative schedule and handouts (expect frequent updates)
Mandatory daily symptom monitoring survey: https://uclasurveys.co1.qualtrics.com/jfe/form/SV_3qRLtouCYKzBbH7
Location and time: CHS 33-105A, Tuesday 1pm-2:50pm and Thursday 1pm-2:50pm.
Zoom: https://ucla.zoom.us/j/96234404896
Slack channel: https://ucla.slack.com/archives/C039NH4NUSG
Readings:
- 50 years of data sicence by David Donoho (2015)
- Julia: a fresh approach to numerical computing by Bezanson, Edelman, Karpinski, and Shah (2017)
- What every computer scientist should know about floating-point arithmetic by David Goldberg
- Top 10 algorithms in the 20th century
Metropolis, Simplex, Krylov, Matrix decomposition, Fortran, QR algorithm, Quicksort, FFT, Integer relation, FMM
| Week | Tuesday | Thursday | Homework |
|---|---|---|---|
| 1 | 3/29 course introduction and logistics [slides: html] | 3/31 computer languages [slides: Binder, html], Julia intro. [slides: Binder, html] | HW1 [ipynb, html] |
| 2 | 4/5 plotting in Julia [slides: Binder, html], Jupyter Notebook [slides: Binder, html] | 4/7 computer arithmetic [slides: Binder, html], algo. intro. [slides: Binder, html] | |
| 3 | 4/12 BLAS [slides: Binder, html], NLA on GPU [slides: Binder, html] | 4/14 triangular systems [slides: Binder, html], GE/LU [slides: Binder, html] | HW2 [ipynb, html] |
| 4 | 4/19 Cholesky [slides: Binder, html], QR (GS, Householder, Givens) [slides: Binder, html] | 4/21 Sweep operator [slides: Binder, html], summary of linear regression [slides: Binder, html] | |
| 5 | 4/26 condition number [slides: Binder, html], iterative methods intro [slides: Binder, html] | 4/28 conjugate gradient [slides: Binder, html] | HW3 [ipynb, html] |
| 6 | 5/3 easy linear system [slides: Binder, html], eigen-decomposition and SVD [slides: Binder, html] | 5/5 optimization intro. [slides: Binder, html] | HW4 [ipynb, html] |
| 7 | 5/10 optimization in Julia [slides: Binder, html] | 5/12 Newton-Raphson, Fisher scoring, GLM, nonlinear regression (Gauss-Newton) [slides: Binder, html], quasi-Newton [slides: Binder, html] | |
| 8 | 5/17 KKT [slides: Binder, html], constrained optimization [slides: Binder, html] | 5/19 EM algorithm [slides: Binder, html] | HW5 [ipynb, html] |
| 9 | 5/24 MM algorithm [slides: Binder, html] | 5/26 LP [slides: Binder, html], QP [slides: Binder, html] | HW6 [ipynb, html] |
| 10 | 5/31 SOCP [slides: Binder, html], SDP [slides: Binder, html], GP [slides: Binder, html] | 6/2 concluding remarks [slides: Binder, html] |