Time: Wednesdays 12:00-3:00 PM | Place: CBIM 22 |
Instructor: Tina Eliassi-Rad | Office hours: Wednesdays 5:30-6:30 PM in CBIM 08 |
TA: Chetan Tonde | TA office hours: Tuesdays 1:00-3:00 PM in Hill 402 |
Course number: 16:198:536 | Credits: 3 |
Prerequisites: Calculus and linear algebra. An introductory course on statistics and probability. Algorithms and programming (MATLAB).
Date |
Content |
Readings |
Notes |
Jan 18 |
Naive Bayes Logistic
Regression |
Bishop 1.3, 1.4, 1.6,
14.4, Mitchell 1, 3, plus follow links in the previous cell. Optional: Discriminative
vs. Generative Models, Guestrin's NB. |
|
Jan 25 |
Linear
Regression Regularization Bias-Variance
Tradeoff Overfitting Cross-Validation |
Bishop 3, 4, Optional:
HTF 3, 4. |
|
Feb 1 |
PAC Learning VC Dimension |
Mitchell 7,
HTF 7, COLT
survey, Generalization Bounds, Schapire's Theoretical ML. Optional: Online Learning.
|
Guest
Lecturer: |
Feb 8 |
Kernel
Methods |
Bishop 6.1,
6.2, 6.3, 7.1 plus follow links in the previous cell. Optional: Bishop 6.4, HTF 6, 12. |
HW#1 Out |
Feb 15 |
Follow links in the previous cell. |
Guest Speakers:
Hanghang
Tong |
|
Feb 22 |
Perceptron Neural
Networks |
Bishop 4.1.7,
5.1, 5.2, 5.3, 5.5. Optional:
Mitchell 4, HTF 11. |
HW #1 Due |
Feb 29 |
Graphical
Models |
Bishop 8, Bayesian Networks. Optional: Mitchell 6, CRF, HMM,
Ghahramani's HMM
& BN, Bishop 13.1, 13.2, 11. |
|
Mar 7 |
Ensemble Methods
In-class Project Pitches |
Bishop 14.1, 14.2, 14.3 plus follow links in the previous cells. Optional: HTF: 10, 15, 16 |
HW #2 Out Project Proposals Due |
Mar 14 |
No Class --
Spring Break |
|
|
Mar 21 |
K-means Expectation
Maximization Mixture of
Gaussians |
Bishop 9.1, 9.2,
9.3, 9.4. Optional: HTF 14; x-means, k-means++ |
|
Mar 28 |
Bishop 12 plus follow links in the previous cell. Optional: M.E. Wall, et al.'s PCA |
HW #2 Due |
|
Apr 4 |
In-class Exam |
Follow links
in the previous cell. Optional: Co-training. |
HW #3 Out |
Apr 11 |
Building Accurate and Comprehensible Classification Models
|
Follow links in the previous cell. |
Guest Speakers:
|
Apr 18 |
Reinforcement
Learning (1), (2) |
Follow links in the previous
cell. |
Guest Lecturer: Michael Littman HW #3 Due |
Apr 25 |
In-class Project Presentations |
|
|
May 2 |
No Class |
|
Project Reports Due |