Welcome! This course is jointly taught by UC Berkeley and the Tsinghua-Berkeley Shenzhen Institute (TBSI).
Notice:
- the password access to all links below is shared in the course WeChat group, please check.
- Slides with annotation in real-time courses are also offered, with title named like "Lect*(annot)".
- Prof. Laurent El Ghaoui (UC Berkeley) <elghaoui [at] berkeley.edu>
- TA Zifeng Wang (TBSI) <wangzf18 [at] mails.tsinghua.edu.cn>
-
[8/12 update] The final project presentation has been decided on Monday 8:30 AM (8/17) !
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[8/10 update] Guideline for the final project.
| Week # | Lec # | Date | Beijing Time | California Time | HW given | HW due | Office Hour |
|---|---|---|---|---|---|---|---|
| 29 | 1 | 2020/7/13 | 8:30am-10:05am | 5:30pm-7:05pm | 1 | ||
| 2 | 2020/7/15 | 8:30am-10:05am | 5:30pm-7:05pm | ||||
| 3 | 2020/7/17 | 8:30am-10:05am | 5:30pm-7:05pm | Yes | |||
| 30 | 4 | 2020/7/20 | 8:30am-10:05am | 5:30pm-7:05pm | |||
| 5 | 2020/7/22 | 8:30am-10:05am | 5:30pm-7:05pm | ||||
| 6 | 2020/7/24 | 8:30am-10:05am | 5:30pm-7:05pm | 2 | 1 | Yes | |
| 31 | 7 | 2020/7/27 | 8:30am-10:05am | 5:30pm-7:05pm | Yes | ||
| 8 | 2020/7/29 | 8:30am-10:05am | 5:30pm-7:05pm | ||||
| 9 | 2020/7/31 | 8:30am-10:05am | 5:30pm-7:05pm | ||||
| 32 | 10 | 2020/8/3 | 8:30am-10:05am | 5:30pm-7:05pm | Yes | ||
| 11 | 2020/8/5 | 8:30am-10:05am | 5:30pm-7:05pm | 3 | 2 | ||
| 12 | 2020/8/7 | 8:30am-10:05am | 5:30pm-7:05pm | ||||
| 33 | 13 | 2020/8/10 | 8:30am-10:05am | 5:30pm-7:05pm | Yes | ||
| 14 | 2020/8/12 | 8:30am-10:05am | 5:30pm-7:05pm | ||||
| 15 | 2020/8/14 | 8:30am-10:05am | 5:30pm-7:05pm | Yes | |||
| 34 | 16 | 8/17 | 8:30am | 3 hours | 3 |
| Day # | Topic | Speaker | Slides / Notes | Real-time Lecture Recordings | HW |
|---|---|---|---|---|---|
| 1 | Intro: optimization models | Laurent El Ghaoui | Lect1 & Lect1(annot) |
Rec1 | HW1 & HW1-Data |
| 2 | Intro: machine learning | Laurent El Ghaoui | Lect2 & Lect2(annot) |
Rec2 | |
| 3 | Covariance estimation | Laurent El Ghaoui | Lect3 & Lect3(annot) |
Rec3 | |
| 4 | Principal components analysis | Laurent El Ghaoui | Lect4 | Rec4 | |
| 5 | Generalized low rank models and matrix completion | Laurent El Ghaoui | Lect5 | Rec5 | |
| 6 | Regression and penalization | Laurent El Ghaoui | Lect6 | Rec6 | |
| 7 | Classification | Laurent El Ghaoui | Lect7 | Rec7 | HW1-sol |
| 8 | Kernel methods, feature engineering and encoding | Laurent El Ghaoui | Lect8 | Rec8 | HW2 & HW2-data |
| 9 | Neural networks | Laurent El Ghaoui | Rec9 | HW2-sol | |
| 10 | Convex functions | Laurent El Ghaoui | Lec10 | Rec10 | |
| 11 | Convex optimization | Laurent El Ghaoui | Lec11 | Rec11 | |
| 12 | Conic models | Laurent El Ghaoui | Lec12 | Rec12 | |
| 13 | Robust optimization | Laurent El Ghaoui | Lec13 | Rec13 | |
| 14 | Affine recourse for multi-period decision models | Laurent El Ghaoui | Lec14 | Rec14 | |
| 15 | Review | Laurent El Ghaoui | Lec15 | Rec15 | |
| 16 | Final Presentation |