- Week 1 (Aug. 26 -- Aug. 30).
Topic: Intro + PAC Learning (MRT, Chapters 1,2)
- Mon (slides): Go over syllabus, Chapter 1
- Wed (slides): MRT, Chapter 1
- Fri (slides): MRT, Section 2.1, HW 1 out
- Week 2: (Sep. 2 -- Sep. 6).
Topic: PAC Learning
- Mon: No class (Labor Day)
- Wed (slides): MRT, Section 2.2
- Fri(slides): MRT, Section 2.3
- Week 3: (Sep. 9 -- Sep. 13)
Topic: Rademacher Complexity & VC Dimension (MRT, Chapter 3)
- Mon: MRT, Section 3.1
- Wed: MRT, Section 3.2
- Fri: MRT, Section 3.3. HW1 due, HW2 out.
- Week 4: (Sep. 16 -- Sep. 20)
Topic: Support Vector Machines (MRT, Chapter 5). SVM slides,Optimization slides.
- Mon: MRT, Sections 5.1,5.2
- Wed: MRT, Section 5.3
- Fri: MRT, Sections 5.4.
- Week 5: (Sep. 23 -- Sep. 27)
Topic: Kernel Methods (MRT, Chapter 6) Kernel methods
- Mon: MRT, Sections 6.1,6.2
- Wed: MRT, Sections 6.3,6.4
- Fri: MRT, Section 6.5.
- Week 6: (Sep 30 -- Oct 4)
Exam 1 + Online Learning
- Mon: MRT, Sections 8.1,8.2. HW 2 due
- Wed: Review
- Fri: Exam 1
- Week 7: (Oct 7 -- Oct 11)
Regression
- Mon: Linear regression slides
- Wed: Beyond linear regression slides
- Fri: Logistic regression slides
- Week 8: (Oct 14 -- Oct 18)
Boosting MRT, Chapter 7. (slides)
- Week 9: (Oct 21 -- Oct 25)
Multi-Class Classification. MRT, Chapter 9. (slides)
No class Friday, Oct. 25 (Homecoming).
- Week 10: (Oct 28 -- Nov 1)
Reinforcement Learning. MRT, Chapter 17. (slides)
- Week 11:
Dimensionality Reduction.
Monday, no class.