Difference between revisions of "Potential Reading"
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| [http://nlp.stanford.edu/courses/NAACL2013/NAACL2013-Socher-Manning-DeepLearning.pdf Deep Learning for NLP (without Magic)] Richard Socher and Chris Manning (2013) || Deep Learning Tutorial Slides || On deep learning in NLP || Arafat | | [http://nlp.stanford.edu/courses/NAACL2013/NAACL2013-Socher-Manning-DeepLearning.pdf Deep Learning for NLP (without Magic)] Richard Socher and Chris Manning (2013) || Deep Learning Tutorial Slides || On deep learning in NLP || Arafat | ||
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Revision as of 12:01, 26 June 2013
Future Readings
Below is a list of papers, articles, etc that should serve as a pool for selecting readings for future CompSem meetings. If you see a paper you would like to read and discuss please post it here, so that we can queue it up.
| Paper | Tags | Rationale | Added by |
|---|---|---|---|
| Probabilistic Topic Models, Steyvers | topic modeling, Latent Dirichlet Allocation (LDA) | Looks like it provides an easier introduction to topic models than the original Blei paper | |
| "Finding Scientific Topics", Steyvers and Griffiths | topic modeling, Latent Dirichlet Allocation (LDA) | Potentially another good explanation of a generative topic model | |
| Dependency Parsing by Belief Propagation Smith, David A. and Jason Eisner (2008) | Belief Propagation, Dependency Parsing | Jason Eisner gave a very interesting keynote talk at the workshop on Semi-Supervised Learning at NAACL 2009 which references this paper | |
| Semi-supervised Learning Literature Survey Xiaojin Zhu (2008) | Semi-supervised learning | I'll be happy if we get through the first few pages | Dima |
| Learning with labeled and unlabeled data Matthias Seeger (2002) | Semi-supervised learning | An older survey | Dima |
| Text Classification from Labeled and Unlabeled Documents using EM Nigram et al. (2000) | Semi-supervised learning | An early semi-supervised learning paper; might be more readable than more recent papers | Dima |
| Frustratingly Easy Domain Adaptation Hal Daume III (2007) | Domain Adaptation | Some kind of magic | Dima |
| Transfer Learning for Text Classification Do and Ng (2005) | Transfer Learning | What in the world is transfer learning? I have no idea but I want to find out. | Dima |
| Using Linguistic Cues for the Automatic Recognition of Personality in Conversation and Text Francois Mairesse, Marilyn Walker, Matthias Mehl and Roger Moore (2007) | content analysis, discourse processing | sort of a different paper for the group | Will |
| Attention, Intentions, and the Structure of Discourse (1986) Barbara J. Grosz, Candace L. Sidner | discourse processing | a classic paper in discourse modeling for computational purposes | Will |
| Deep Learning for NLP (without Magic) Richard Socher and Chris Manning (2013) | Deep Learning Tutorial Slides | On deep learning in NLP | Arafat |
For some ideas you might look at other reading groups:
* Johns Hopkins NLP Reading Group * Stanford NLP Reading Group
