| Week: Date
| Topics and slides
| Readings
| Assignment
| Due
|
| W1: Jan 3 (T)
| Course overview
Information theory
| M&S 2.2
Probability theory
Overview of Classification task
Using Mallet
Patas and Condor Submit
| Hw1
|
|
| W1: Jan 5 (R)
| Decision Tree
| Decision Tree Tutorial
|
|
|
| W2: Jan 10 (T)
| Finish Decision Tree
|
| Hw2
(slides)
| Hw1
|
| W2: Jan 12 (R)
| Naive Bayes
| M 13.2-13.4
(McCallum and Nigam, 1998)
|
|
|
| W3: Jan 17 (T)
| Finish Naive Bayes
kNN
| kNN intro
| Hw3
(slides)
| Hw2
|
| W3: Jan 19 (R)
| Feature Selection
| M 13.5
| Reading #1: MaxEnt
|
|
| W4: Jan 24 (T)
| Chi-square test
Unit #1 recap
| Chi square test tutorial
| Hw4
(slides)
| Hw3
|
| W4: Jan 26 (R)
| MaxEnt I: main concepts
| (Berger et al., 1996)
(Ratnaparkhi, 1997)
|
| Reading #1
|
| W5: Jan 31 (T)
| MaxEnt II: modeling and decoding
|
| Hw5 (slides)
| Hw4
|
| W5: Feb 2 (R)
| MaxEnt III: Training
| (Klein and Manning, 2003)
|
|
|
| W6: Feb 7 (T)
| MaxEnt IV: case study and
beam search
| (Ratnaparkhi, 1996)
| Hw6
(slides)
| Hw5
|
| W6: Feb 9 (R)
| CRF
| (Sutton and McCallum, 2006)
| Reading #2
|
|
| W7: Feb 14 (T)
| Transformation-based learning
| (Brill, 1995)
|
| Hw6
|
| W7: Feb 16 (R)
| Hyperplane
SVM I: Linear SVM
| M 15
| Hw7
(slides)
| Reading #2
|
| W8: Feb 21 (T)
| Complete SVM I
| M 15
| Reading #3
|
|
| W8: Feb 23 (R)
| SVM II: non-linear SVM
| M 15
|
| Hw7
|
| W9: Feb 28 (T)
| Multi-class classification
Using libSVM
SVM III: Tree kernel
| (Collins and Duffy, 2001)
| Hw8
| Reading #3
|
| W9: March 2 (R)
| SVM IV: Transductive SVM
| (Joachims, 1999)
|
|
|
| W10: March 7 (T)
| Semi-supervised learning
| (Zhu, 2008)
(McClosky et al., 2006)
| Hw9
| Hw8 (due 3/8)
|
| W10: March 9 (R)
| Summary
|
|
| Hw9 (due 3/15)
|