Instructor:
Dan Gildea (Office hours: Mon 2:003:00pm, Wed 1:002:00pm or by appointment)
TA: Linfeng Song
Location: Tu/Th 11:05am12:20pm, CSB 601.
Homeworks
Recommended resources:
Syllabus
On  we will cover  which means that after class you will understand  if before class you have read 
8/30 
Hidden Markov Models 
viterbi, forward
 JM 6 
9/5 
Perceptron for Tagging 
NLP = ML + DP
 Collins 2002 
9/7 
CRFs 
f  E[f]
 McCallum 2001 
9/12 
Max Margin Learning 
subgradients
 Tsochantaridis 2004, Ratliff 2006 
9/14 
EM for HMM 
 JM 6 
9/19 
latent CRF 
 
9/21 
Ngrams 
GoodTuring, Katz, KneserNey
 
9/26 
Context Free Grammars 
highest prob string, infinite trees
 JM 13 
9/28 
Context Free Grammars 
viterbi, insideoutside
 
10/3 
Context Free Grammars 
viterbi, insideoutside
 
10/5 
Parsing 
minimum risk decoding, crf parsing
 Finkel 08 
10/10 
Fall Break 
 
10/12 
Parsing 
em, latent crf, maxmargin
 
10/17 
Treebanks 
right node raising
 JM 12 
10/19 
Search 
beam search, A*
 
10/24 
Dependency parsing 
 
10/26 
Review 
 
10/31 
Midterm 


11/2 
Midterm Solutions 
 
11/7 
Machine Translation
 model 1, 2, 3
 Brown 1993 
11/9 
Machine Translation
 decoding
 Koehn et al. 2003 Galley 2004, Chiang 05 
11/14 
Neural Machine Translation 
LSTM
 Sutskever 2014, Bahdanau 2014 
11/16 
Machine Translation 
minimum risk training
 Papineni 2002, Shen 2016 
11/21 
Semantics 
word2vec
 Mikolov 2013, Pennington 2014 
11/28 
Semantics 
lambda calculus
 JM 20, Zettlemoyer 2005, Liang 2011 
11/30  Deep Learning 
neural symbolic machines
 Liang et al., 2017, 
12/5 
Deep Learning for parsing 
tabularization
 Socher 2013, Shi 2017 
12/7 
Something fun 
expected products of counts
 Pauls 2009 
12/12 
no class 
 
Final Exam: Thursday, December 21, 47pm, CSB 601.
Grading
 Final exam: 35%
 Homeworks: 35%
 Midterm: 25%
 Class participation: 5%
 No late homework
 Programming assignments must be in python, and must run on class account
gildea @ cs rochester edu
December 7, 2017
