Computational Linguistics I (INST 735 / CMSC 723 / LING 723)

Logistics

Location CSIC 3117
Time Mon./Wed. 15:30pm - 16:45pm
Webpage http://umiacs.umd.edu/~jbg/teaching/CMSC_723/
Mailing List https://piazza.com/umd/fall2018/cmsc723
Text Natural Language Processing
Syllabus https://docs.google.com/document/d/1nTkyPlijzNs0ORk7GXbN2ec4X0eoIT5v655gW2RawgM/pub

People

Professor

Jordan Boyd-Graber
AVW 3153
Office Hours (AVW 3155): Starting Sept. 4, Mondays 14:00 - 15:00 and by appointment

Teaching Assistants

Chen Zhao: AVW 4424, Thursdays 15:00-16:00 Ahmed Elgohary: AVW 4185, Mondays 13:00-14:00

Schedule

Date In-Class Topic Assignment Due Lecture
Mon 27. Aug Introduction to the course, Probability, and Python [Intro Video]
Optional Readings:
Wed 29. Aug Probabilistic Classification (Ahmed) [Slides: NB LR Ex] [Video: NB LR]
Readings:
  • NLP Chapter 2
Optional:
Mon 3. Sep No Class: Labor Day!
Wed 5. Sep Classification II [Slides: SG Perceptron SVM Ex] [Video: SGD Support Vector Machines Perceptron] [In Class]
Readings:
  • NLP Chapter 2
Fri 7. Sept HW 0 Limericks
Mon 10. Sep Deep Learning [Slides: Deep Ex] [Video: Deep Backprop] [In Class]
Readings:
  • NLP Chapter 3
Wed 12. Sep Course Project (Chen) [Video]
Readings:
Mon 17. Sep Distributional Semantics (Word2Vec) [Video: Intution Algorithm Evaluation] [Slides: Intro word2vec Eval Ex] [Class]
Readings:
  • NLP Chapter 14
Wed 19. Sep Language Models [Video: Intro Backoff] [Slides: Intro Backoff Ex] [Class]
Readings: Optional:
Fri 21. Sept HW 1 Classification
Mon 24. Sep Frameworks [Video: Intro Pytorch DAN] [Slides: Compgraph Code DAN Ex] [Class]
Readings:
Wed 26. Sep Classification and Feature Engineering [Video: Classification, Examples: A B] [PDF: Classification Examples: A B] [Class]
Readings:
Fri 28. Sept HW 2 Language Models
Mon 1. Oct Topic Models [Video: Intro Evaluation Gibbs Sampling] [PDF: Topic Models Gibbs Sampling Ex] [Class]
Readings:
Mon 3. Oct Part of Speech [Video: Tagging Perceptron Structured Preceptron] [Slides: POS Viterbi Perceptron Ex] [Class]
Readings:
Mon 8. Oct Neural Sequence Models [Video: RNN LSTM] [PDF: RNN LSTM Example] [Class]
Readings:
  • NLP 6.3
  • NLP 7.6
Wed 10. Oct FSTs and Morphology [Video] [PDF] [Class]
Readings:
  • NLP 9
Fri 12. Oct HW 3 Deep Learning
Mon 15. Oct Constituency Parsers [Video] [PDF PCFG Ex] [Class]
Readings:
  • NLP 10
Wed 17. Oct Dependency Grammars [Video: Intro Shift/Reduce] [PDF: Intro Shift/Reduce Ex] [Class]
Readings:
  • NLP 11
Fri 19. Oct HW 4 Topic Models
Mon 22. Oct Named Entities and Coreference [PDF: Entities Coref QA]
Readings:
Wed 24. Oct Midterm Review [PDF]
Fri 26. Oct Project Proposal Due Proposal
Mon 29. Oct Midterm
Wed 31. Oct Project Workshop
Fri 2. Nov HW 5 Parsing
Mon 5. Nov No Class (EMNLP, but Chen will be in the room to talk about projects)
Wed 7. Nov Machine Translation [Video: Word-Based Phrase Neural] [PDF: Word Phrase Neural Ex]
Readings:
  • NLP 18
Mon 12. Nov RL for NLP [Video: Introduction Imitation Policy Gradient] [PDF A B C D]
Readings:
Wed 14. Nov Grabbag I: VAE/GANs, Computational Social Science, Domain Adaptation (Non-flipped) [CSS GANs ]
Readings:
Mon 19. Nov Grabbag II: Coding for NLP, RL for MT, IR + Machine Reading (Non-flipped)
Mon 26. Nov Reading and Reviewing NLP Papers [LaTeX Audiences Reviewing Project Discussion]
Wed 28. Nov AI in Society [Video Discussion]
Readings:
Fri 30. Nov HW 6 Sequence
Mon 3. Dec Project Workshop and Playtest [Project Questions Game]
Wed 5. Dec Final Project Presentations I
Mon 10. Dec Final Project Presentations II
Fri 14. Dec 13:30-15:30 Final Exam