Date |
Class Period & Lecture Topic |
Reading |
Assignment |
Jan 04 |
1. Syllabus, policies, business |
|
|
Jan 06 |
No meeting (ICCCX) |
|
Topic Suggestions |
Jan 11 |
2. Sparse coding |
Sparse Coding papers |
|
Jan 13 |
3. Sparse coding |
|
|
Jan 18 |
No meeting (holiday) |
|
|
Jan 22 |
4. Sparse coding (Langrange/Dual) |
|
|
Jan 25 |
5. Deep networks |
Deep Networks papers |
|
Jan 27 |
6. Deep networks |
|
|
Feb 01 |
7. Markov random fields |
|
|
Feb 03 |
8. Markov random fields |
Markov Random Fields papers |
|
Feb 08 |
No meeting (NSF) |
|
|
Feb 10 |
9. Snow day |
|
|
Feb 12 |
10. Structure SVMs |
Structured SVM papers |
|
Feb 15 |
No meeting (holiday) |
|
|
Feb 16 |
11.Structure SVMs |
|
|
Feb 17 |
12.Feature Selection (Rob) |
Feature Selection papers |
|
Feb 22 |
13. Feature Selection (Rob) |
|
|
|
Midterm (Feb 23–26, Take Home) |
Feb 24 |
14. No meeting (midterm) |
|
|
Mar 01 |
15. SVM Model Selection (Beau) |
SVM Model Selection papers |
|
Mar 03 |
16. SVM Model Selection (Beau) |
|
|
Mar 08 |
17. NeuroEvolution (Dave) |
NeuroEvolution papers |
|
Mar 10 |
18. NeuroEvolution (Dave) |
|
|
Mar 15 |
19. POMDP (Mike) |
POMDP papers |
|
Mar 17 |
20. POMDP (Mike) |
|
|
Mar 22 |
21. Deep Transfer (Spencer) |
Deep Transfer papers |
|
Mar 24 |
22. Deep Transfer (Spencer) |
|
|
Mar 29 |
23. Hierarchical Reinforcement Learning (Brian) |
Hierarchical Reinforcement Learning papers |
|
Mar 31 |
24. Hierarchical Reinforcement Learning (Brian) |
|
|
Apr 05 |
25. Active Learning (Sabra) |
Active Learning papers |
|
Apr 07 |
26. Active Learning (Sabra) |
|
|
Apr 12 |
27. Culinary Search |
Culinary Search papers |
|
Apr 17 |
Final (7:00–10:00am in class) |