POSSIBLE PAPERS
FALL 2005

• Rie Ando; Tong Zhang
  A High-Performance Semi-Supervised Learning Method for Text Chunking
  http://acl.ldc.upenn.edu/P/P05/P05-1001.pdf
  


• Ryan McDonald; Koby Crammer; Fernando Pereira
  Online Large-Margin Training of Dependency Parsers
  http://acl.ldc.upenn.edu/P/P05/P05-1012.pdf


• Maayan Geffet; Ido Dagan
  The Distributional Inclusion Hypotheses and Lexical Entailment
  http://acl.ldc.upenn.edu/P/P05/P05-1014.pdf


• Regina Barzilay; Mirella Lapata
  Modeling Local Coherence: An Entity-Based Approach
  http://acl.ldc.upenn.edu/P/P05/P05-1018.pdf


• (Related paper)
  Automatic Evaluation of Text Coherence: Models and Representations
  Mirella Lapata and Regina Barzilay
  IJCAI-05, page 1085
  http://www.ijcai.org/papers/0505.pdf


• David Chiang
  A Hierarchical Phrase-Based Model for Statistical Machine Translation
  http://acl.ldc.upenn.edu/P/P05/P05-1033.pdf


• I. Tsochantaridis, T. Hofmann, T. Joachims, and Y. Altun
  Support Vector Machine Learning for Interdependent and Structured Output Spaces
  Proceedings of the International Conference on Machine Learning (ICML), 2004.
  http://www.cs.cornell.edu/People/tj/publications/tsochantaridis_etal_04a.pdf


• (Must follow the previous one)
  A Support Vector Method for Multivariate Performance Measures
  Thorsten Joachims, Cornell University
  http://www.cs.cornell.edu/People/tj/publications/joachims_05a.pdf


• Mark Herbster, Massimiliano Pontil, Lisa Wainer
  Online Learning over Graphs
  http://www.cs.ucl.ac.uk/staff/M.Herbster/pubs/gpercicmlfin.pdf


• Alexandru Niculescu-Mizil, Rich Caruana
  Predicting Good Probabilities With Supervised Learning
  http://www.machinelearning.org/proceedings/icml2005/papers/079_GoodProbabilities_NiculescuMizilCaruana.pdf


• Dan Roth, Wen-tau Yih
  Integer Linear Programming Inference for Conditional Random Fields
  http://l2r.cs.uiuc.edu/~danr/Papers/RothYi05.pdf


• Hal Daume III, Daniel Marcu
  Learning as Search Optimization: Approximate Large Margin Methods for Structured Prediction
  http://www.isi.edu/~marcu/papers/daume05laso.pdf


• Maloberti, J., & Sebag, M. (2004).
  Fast theta-subsumption with constraint satisfaction algorithms
  Machine Learning, 55, 137-174.
  http://www.lri.fr/~sebag/REF/MLJ_Django.ps


• Alan Fern
  A Simple-Transition Model for Relational Sequences
  IJCAI-05, page 696
  http://www.ijcai.org/papers/0509.pdf


• Yuhong Guo, Russell Greiner, and Dale Schuurmans
  Learning Coordination Classifiers
  IJCAI-05, page 714
  http://www.ijcai.org/papers/1585.pdf


• Doug Downey, Oren Etzioni, and Stephen Soderland
  A Probabilistic Model of Redundancy in Information Extraction
  IJCAI-05, page 1034
  http://www.ijcai.org/papers/1390.pdf


• Alon Altman and Moshe Tennenholtz
  On the Axiomatic Foundations of Ranking Systems
  IJCAI-05, page 917
  http://www.ijcai.org/papers/0374.pdf


• Bart Goethals, Eveline Hoekx, Jan Van den Bussche
  Mining Tree Queries in a Graph
  KDD'05
  http://www.adrem.ua.ac.be/~goethals/publications/tqm.pdf