Difference between revisions of "MLReadingGroup"

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(Schedule (Spring 2008))
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We maintain an announcement/discussion list for the reading group. You may sign up for the list [https://lists.cs.princeton.edu/mailman/listinfo/ml-reading/ here].
 
We maintain an announcement/discussion list for the reading group. You may sign up for the list [https://lists.cs.princeton.edu/mailman/listinfo/ml-reading/ here].
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==Schedule (Fall 2008) ==
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Our weekly meetings are '''Mo 1:00-5:00pm''' on the 3rd floor of the CS building (CS 302).
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* Graphical Models, exponential families, and variational inference
  
  
 
==Schedule (Spring 2008) ==
 
==Schedule (Spring 2008) ==
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Our weekly meetings are '''Tue 1:00-2:30pm''' in the AI lab on the 4th floor of the CS building (CS 431).
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Schedule of topics:
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* 13 May 2008
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** Topic: Maximum Entropy Discrimination
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** Leader: Chong Wang
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** Main Paper: [http://people.csail.mit.edu/tommi/papers/JaaMeiJeb-nips99.ps Tommi Jaakkola, Marina Meila, and Tony Jebara, Maximum Entropy Discrimination, In ''NIPS'' 1999.]
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** Long Version: [http://people.csail.mit.edu/tommi/papers/maxent.ps Tommi Jaakkola, Marina Meila, and Tony Jebara, Maximum Entropy Discrimination, Technical Report AITR-1668, MIT, 1999]
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* 6 May 2008
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** Topic: Feature selection for relational data
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** Leader: Jonathan Chang
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** Main Paper: [http://citeseer.ist.psu.edu/635777.html Jensen, Neville, and Hay (2003), Avoiding Bias when Aggregating Relational Data with Degree Disparity]
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** Background: [http://citeseer.ist.psu.edu/jensen02linkage.html Jensen and Neville (2002), Linkage and Autocorrelation Cause Feature Selection Bias in Relational Learning]
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* 22 April 2008
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** Topic: Game theory
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** Leader: Indraneel Mukherjee
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** Main Paper: [http://projecteuclid.org/DPubS/Repository/1.0/Disseminate?view=body&id=pdf_1&handle=euclid.pjm/1103044235 An Analog of the Minimax Theorem for Vector Payoffs]
  
Our weekly meetings are '''Tue 1:00-2:30pm''' in the AI lab on the 4th floor of the CS building (CS 431).
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* 15 April 2008
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** Topic: Conditional Random Fields
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** Leader: Berk Kapicioglu
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** Main Paper: [http://www.seas.upenn.edu/~strctlrn/bib/PDF/crf.pdf J. Lafferty, A. McCallum, and F. Pereira (2001), Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data]
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* 8 April 2008
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** Topic: Online Feature Selection
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** Leader: Melissa Carroll
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** Main Paper: [http://jmlr.csail.mit.edu/papers/volume7/zhou06a/zhou06a.pdf Jing Zhou, Dean P. Foster, Robert A. Stine, and Lyle H. Ungar (2006), Streamwise Feature Selection]
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** Background Paper: [http://www-stat.wharton.upenn.edu/~stine/research/smr.pdf Robert A. Stine (2003), Model Selection using Information Theory and the MDL Principle]
  
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* 1 April 2008
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** Topic: Reinforcement learning and online learning
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** Leader: Umar Syed
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** Main Paper: [http://books.nips.cc/papers/files/nips20/NIPS2007_0631.pdf Alexander Strehl and Michael Littman (2008), Online Linear Regression and Its Application to Reinforcement Learning]
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** Background Paper: [http://citeseer.ist.psu.edu/638941.html Peter Auer (2002), Using Confidence Bounds for Exploitation-Exploration Trade-offs]
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** Background Paper: [http://citeseer.ist.psu.edu/443693.html Ronen I. Brafman and Moshe Tennenholtz (2002), R-max – A General Polynomial Time Algorithm for Near-Optimal Reinforcement Learning]
  
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* 25 March 2008
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** Topic: Network/Relational Learning
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** Leader: Jonathan Chang 
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** Main Paper: [http://arxiv.org/abs/0803.1628v1 Janne Sinkkonen, Janne Aukia, Samuel Kaski.  Component models for large networks]
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** Background Paper: [http://citeseer.ist.psu.edu/cohn01missing.html D Cohn, T Hofmann.  The Missing Link-A Probabilistic Model of Document Content and Hypertext Connectivity]
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** Background Paper: [http://arxiv.org/abs/0705.4485 Edoardo M Airoldi, David M Blei, Stephen E Fienberg, Eric P Xing.  Mixed membership stochastic blockmodels]
  
Schedule of topics:
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* 11 March 2008
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** Topic: Online learning with experts
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** Leader: Indraneel Mukherjee
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** Paper: [http://nagoya.uchicago.edu/~jabernethy/Binning.pdf Jacob Abernethy, John Langford, Manfred Warmuth. The Binning Algorithm ]
  
 
* 04 March 2008
 
* 04 March 2008
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** Leader: Jordan Boyd-Graber
 
** Leader: Jordan Boyd-Graber
 
** Paper: [http://books.nips.cc/papers/files/nips20/NIPS2007_0964.pdf Toutanova, Kristina and Johnson, Mark. A Bayesian LDA-based model for semi-supervised part-of-speech tagging.  (2007)]
 
** Paper: [http://books.nips.cc/papers/files/nips20/NIPS2007_0964.pdf Toutanova, Kristina and Johnson, Mark. A Bayesian LDA-based model for semi-supervised part-of-speech tagging.  (2007)]
** Paper: [http://portal.acm.org/citation.cfm?id=1219884 Smith, Noah and Eisner, Jason.  Contrastive Estimation: Training Log-Linear Models on Unlabeled Data]
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** Paper: [http://portal.acm.org/citation.cfm?id=1219884 Smith, Noah and Eisner, Jason.  Contrastive Estimation: Training Log-Linear Models on Unlabeled Data.  (2005)]
 
 
 
 
  
 
* 26 February 2008
 
* 26 February 2008
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=== Students ===
 
=== Students ===
 
* Indraneel Mukherjee, CS
 
* Indraneel Mukherjee, CS
* Zafer Barutcuoglu, CS
 
 
* Jordan Boyd-Graber, CS
 
* Jordan Boyd-Graber, CS
 
* Joseph Calandrino, CS
 
* Joseph Calandrino, CS
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* Berk Kapicioglu, CS
 
* Berk Kapicioglu, CS
 
* Umar Syed, CS
 
* Umar Syed, CS
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* Chong Wang, CS
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* Sina Jafarpour, CS
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* Sean Gerrish, CS
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* Richard Socher, CS

Latest revision as of 08:18, 3 February 2009

Machine Learning Reading Group

Welcome to the wiki of the machine learning reading group.

Mailing list

We maintain an announcement/discussion list for the reading group. You may sign up for the list here.

Schedule (Fall 2008)

Our weekly meetings are Mo 1:00-5:00pm on the 3rd floor of the CS building (CS 302).

  • Graphical Models, exponential families, and variational inference


Schedule (Spring 2008)

Our weekly meetings are Tue 1:00-2:30pm in the AI lab on the 4th floor of the CS building (CS 431).


Schedule of topics:

Schedule (Fall 2007)

Our weekly meetings are Wed 4:00-5:30pm in the AI lab on the 4th floor of the CS building (CS 431).

Schedule of topics:

Additional topics:

  • relational network models
  • DP + parse trees
  • online learning
  • semi-supervised learning
  • stochastic gradient
  • convex optimizing
  • parallel learning
  • game theory

Schedule (Spring 2007)

Our weekly meetings are Thu 1:30-3:00pm in the AI lab on the 4th floor of the CS building (CS 431).

Schedule of topics:

Schedule (Fall 2006)

Our weekly meetings are Fridays, 3pm to 5pm, in CS 402.

Scheduled readings:

Proposed Topics and Papers

Please add further topics, suggest papers for particular topics, etc. here.

Participants

(Participants, please add your name to the list below.)

Faculty

  • David Blei
  • Rob Schapire

PostDocs

  • Edo Airoldi, LSI & CS
  • Florian Markowetz, LSI

Students

  • Indraneel Mukherjee, CS
  • Jordan Boyd-Graber, CS
  • Joseph Calandrino, CS
  • Melissa Carroll, CS
  • Jonathan Chang, EE
  • Miroslav Dudik, CS
  • Rebecca Fiebrink, CS
  • Berk Kapicioglu, CS
  • Umar Syed, CS
  • Chong Wang, CS
  • Sina Jafarpour, CS
  • Sean Gerrish, CS
  • Richard Socher, CS