Candidacy Examination Resources

Committee

• Bill Noble (advisor)
• Christina Leslie
• Tony Jebara

Time and Location

Literature Search

Background

• On the exponential value of labeled samples
  V. Castelli and T.M. Cover (1995)


• The value of unlabeled data for classification
  Tong Zhang (2000)


• Learning with labeled and unlabeled data
  Matthias Seeger (2001)


• Unlabeled data can degrade classification performance of generative classifiers
  Fabio G. Cozman and Ira Cohen (2002).

Transduction

• Statistical Learning Theory (Chapter 8)
  Vladimir Vapnik (1998).


• Learning by transduction
  A. Gammerman, V. Vovk, V. Vapnik (1998)


• Semi-supervised support vector machines
  Kristin Bennett, Ayhan Demiriz (1998)


• Transductive inference for text classification using support vector machines
  Thorsten Joachims (1999)


• Maximum Entropy Discrimination
  Tommi Jaakkola, Marina Meila, and Tony Jebara (1999).


• Optimization approaches to semi-supervised learning
  Ayhan Demiriz, Kristin Bennett (2000)


• Bayesian transduction
  Thore Graepel, Ralf Herbrich, Klaus Obermayer (2000)


• Transductive and Inductive Methods for Approximate Gaussian Process Regression
  Anton Achwaighofer, Volker Tresp (2002).


• Learning from Labeled and Unlabeled Data using Graph Mincuts
  Avrim Blum, Shuchi Chawla (2001).


• Partially labeled classification with Markov random walks
  Martin Szummer, Tommi Jaakkola (2002)


• Learning the kernel matrix with semi-definite programming
  Gert Lanckriet, Nello Christianini, Peter Bartlett, Laurent El Ghaoui, Michael I. Jordan. (2002).

Related Topics

• Combining labeled and unlabeled data with co-training
  Avrim Blum, Tom Mitchell (1998)


• The role of unlabeled data in supervised learning
  Tom Mitchell (1999)


• Understanding the behavior of co-training
  Kamal Nigam, Rayid Ghani (1999)


• Text classification from labeled and unlabeled documents using EM
  Kamal Nigam, Andrew McCallum, Sebastian Thrun, Tom Mitchell (1999)


• Enhancing supervised learning with unlabeled data
  Sally Goldman, Yan Zhou (2000)


• Kernel expansions with unlabeled examples
  Martin Szummer, Tommi Jaakkola (2001)


• Support vector machine active learning with application to text classification
  Simon Tong, Daphne Koller (2001)

Slides