| Date | 
Lecture | 
Notes etc | 
|  Wed. January 19th | 
 Lecture 1: Introduction, hidden Markov models, log-linear models
 | 
  Slides part 1
  (introduction, hidden Markov models),
  Slides part 2 (log-linear
  models).
 
Background reading: J&M Chapter 5 on part-of-speech tagging, J&M
  sections 6.1-6.4 (HMMs), J&M 6.6-6.7 (Log-linear models). Note that
there are a couple of typos in section 6.7 in log-linear models, described
here.
  | 
| Wed. January 26th | 
 Lecture 2: Log-linear models, MEMMs, CRFs 
 | 
  Slides
(log-linear models, MEMMs, CRFs)
 
Required reading:
note on log-linear models, MEMMs, and CRFs
  | 
| Wed. February 2nd | 
 Lecture 3: Discriminative Dependency Parsing 
 | 
  Slides
(Discriminative dependency parsing)
 
Readings:
 
McDonald, Crammer and Pereira, 2005 (on projective discriminative
dependency parsing)
 
McDonald, Pereira, Ribarov, Hajic, 2005
 (on non-projective discriminative
dependency parsing, including a description of the decoding algorithm
for directed spanning trees)
 
Koo, Globerson, Carreras, Collins, 2007
 (on calculating marginals using the matrix-tree theorem).
  | 
| Wed. February 9th | 
 Lecture 4: CRFs for CFG parsing, the
structured perceptron, belief propagation 
 | 
  Slides
 | 
| Wed. February 16th | 
 Lecture 5:
Dual Decomposition (part I)
 
 | 
  Slides (4 per page),
  Slides (1 per page), with animations
 
Reading: 
Koo et al., EMNLP 2010
  | 
| Wed. February 23rd | 
 Lecture 6:
Dual Decomposition (part II)
 
 | 
  Slides (part 1),
  Slides (part 2)
 
Reading: 
Rush et al., EMNLP 2010
  | 
| Wed. March 2nd | 
 Lecture 7
 
 | 
Student project proposal presentations.
 | 
| Wed. March 9th | 
 Lecture 8:
Statistical Machine Translation
 
 | 
  Slides on phrase-based models(4 per page),
  Slides on Hiero,
  Koehn and Knight tutorial.
 
Readings: 
Chiang, 2007, 
Koehn et al., 2003.
  | 
| Wed. March 16th | 
 Lecture 9:
 
 | 
 | 
| Wed. March 30th | 
 Lecture 10:
Lagrangian relaxation for MT decoding
 
 | 
  Slides
 | 
| Wed. April 6th | 
 Lecture 11: Discriminative models for MT/Brown
clustering and semi-supervised learning
 
 | 
  Slides part 1,
  Slides part 2
 | 
| Wed. April 13th | 
 Lecture 12: Yarowsky's algorithm, cotraining
 
 | 
  Slides part 1,
  Slides part 2
 | 
| Wed. April 20th | 
 Lecture 13:
 
 | 
 | 
| Wed. April 27th | 
 Lecture 14:
 
 | 
 |