Schedule

Unit Focus Screencasts/Readings Assignments
Mar 28
  1. Course overview
    [slides]
  1. Course set-up
  1. Ng & Zelle 1997
  2. Ferrucci et al. 2010
  3. Mitchell 2004
  4. Podcast: The challenge and promise of artificial intelligence [video version]
  5. Levesque 2013
  1. HW 1 [final section of the notebook for this unit; due Apr 6]
Mar 30
  1. Distributional word representations
  1. Overview of notebook and concepts; exploration of the semantic orientation method
  1. Turney and Pantel 2010
  2. Screencast: Overview [slides]
  3. Screencast: Vector comparison [slides]
  5. Screencast: Reweighting [slides]
  7. Screencast: Dimensionality reduction [slides]
  8. Talk: t-SNE (van der Maaten)
Apr 4
  1. Word similarity bake-off
Apr 6
  1. Supervised sentiment analysis
  1. Overview of notebook and concepts; initial feature functions and evaluations
  1. Optional: Tutorial videos on supervised learning
  2. Socher et al. 2013
  1. HW 2 [final section of the notebook for this unit; due Apr 13]
Apr 11
  1. Stanford Sentiment Treebank bake-off
Apr 13
  1. Workshop 1
    [slides]
  1. Project planning
  1. Domingos 2012
  2. Resnik and Lin 2010
  3. Smith 2011, Appendix B
  1. HW 3 [due Apr 25]
Apr 18
  1. Relation extraction [slides]
  1. Hand-built and supervised
  1. Jurafsky and Martin 2009, §22.1-22.2
  2. Snow et al. 2005
  3. Mintz et al. 2009
  4. Banko et al. 2007
  5. Fader et al. 2011
  6. Yao et al. 2012
Apr 20
  1. Distant and unsupervised
Apr 25
  1. Natural language inference
  1. Word-level entailment with neural networks (bake-off)
  1. Stanford AI Lab Deep Learning Tutorial
  2. Goldberg 2015
  3. Bowman et al. 2015a
  4. Bowman et al. 2015b
  5. Rocktäschel et al. 2015
  1. HW 4 [final section of the NLI notebook; due May 4].
  2. Lit review due May 4
Apr 27
  1. Guest lecture: Sam Bowman: Modeling natural language semantics with learned representations
May 2
  1. Natural language inference notebook
  2. Models for NLI (slides)
May 4
  1. Semantic parsing
    [slides]
  1. SippyCup codebase
  2. Overview and concepts
  3. SippyCup unit 0
  1. Screencast: Core concepts for semantic parsing [slides]
  2. Screencast: Semantic parsing models [slides]
  3. Liang and Potts 2015
  4. Zettlemoyer & Collins 2005
  5. Liang et al. 2011 (Or if you're ambitious, the longer version: Liang et al. 2013)
  6. Talk: Learning dependency-based compositional semantics (Percy Liang)
  1. HW 5 [due May 16]
May 9
  1. SippyCup unit 1
  2. Learning an alien language (bake-off)
May 11
  1. SippyCup unit 2
  2. SippyCup unit 3
  3. Date parsing bake-off
May 16
  1. Workshop 2 [slides]
  1. Writing up and presenting your work
  1. Stuart Shieber on reporting research results
  2. David Goss on math style
May 18
  1. Pragmatic agents
  1. Jiwei Li: Neural dialogue generation
  2. Will Monroe: Pragmatic description generation with cooperative networks
May 23
  1. Project work (teaching team available in the classroom)
  1. Project milestone due May 23
May 25
  1. Student presentations 1
May 30
  1. Memorial Day (no class)
Jun 1
  1. Student presentations 2
Jun 6
11:59pm

FINAL PROJECT DUE