| 1 |
Introduction and Overview |
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| 2 |
Parsing and Syntax I |
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| 3 |
Smoothed Estimation, and Language Modeling |
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| 4 |
Parsing and Syntax II |
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| 5 |
The EM Algorithm |
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| 6 |
The EM Algorithm Part II |
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| 7 |
Lexical Similarity |
Homework 1 due |
| 8 |
Lexical Similarity (cont.) |
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| 9 |
Log-Linear Models |
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| 10 |
Tagging and History-based Models |
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| 11 |
Grammar Induction |
Homework 2 due |
| 12 |
Computational Modeling of Discourse |
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| 13 |
Text Segmentation |
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Midterm |
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| 14 |
Local Coherence and Coreference |
Homework 3 due |
| 15 |
Machine Translation |
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| 16 |
Machine Translation (cont.) |
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| 17 |
Machine Translation (cont.) |
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| 18 |
Graph-based Methods for NLP Applications |
Homework 4 due |
| 19 |
Word Sense Disambiguation |
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| 20 |
Global Linear Models |
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| 21 |
Global Linear Models Part II |
Homework 5 due |
| 22 |
Dialogue Processing |
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| 23 |
Dialogue Processing (cont.) |
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| 24 |
Guest Lecture: Stephanie Seneff |
Homework 6 due |
| 25 |
Text Summarization |
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Final Exam |
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