Deterministic and Statistical Methods in Machine Learning 2004: Sheffield, UK

• Christopher M. Bishop, Ilkay Ulusoy:
  Object Recognition via Local Patch Labelling. 1-21
  
• Samy Bengio, Hervé Bourlard:
  Multi Channel Sequence Processing. 22-36
  
• Gavin C. Cawley, Nicola L. C. Talbot, Gareth J. Janacek, Michael Peck:
  Bayesian Kernel Learning Methods for Parametric Accelerated Life Survival Analysis. 37-55
  
• Neil D. Lawrence, John C. Platt, Michael I. Jordan:
  Extensions of the Informative Vector Machine. 56-87
  
• Tom Shorrock, David MacKay, Chris Ball:
  Efficient Communication by Breathing. 88-97
  
• Dharmesh M. Maniyar, Ian T. Nabney:
  Guiding Local Regression Using Visualisation. 98-109
  
• Roderick Murray-Smith, Barak A. Pearlmutter:
  Transformations of Gaussian Process Priors. 110-123
  
• Petra Kudová, Roman Neruda:
  Kernel Based Learning Methods: Regularization Networks and RBF Networks. 124-136
  
• Jonathan Goldstein, John C. Platt, Christopher J. C. Burges:
  Redundant Bit Vectors for Quickly Searching High-Dimensional Regions. 137-158
  
• Stephen Roberts, Rizwan Choudrey:
  Bayesian Independent Component Analysis with Prior Constraints: An Application in Biosignal Analysis. 159-179
  
• Jeremy Rogers, Steve R. Gunn:
  Ensemble Algorithms for Feature Selection. 180-198
  
• Peter Sollich:
  Can Gaussian Process Regression Be Made Robust Against Model Mismatch? 199-210
  
• Peter Sollich, Christopher K. I. Williams:
  Understanding Gaussian Process Regression Using the Equivalent Kernel. 211-228
  
• Yi Sun, Mark Robinson, Rod Adams, Paul Kaye, Alistair G. Rust, Neil Davey:
  Integrating Binding Site Predictions Using Non-linear Classification Methods. 229-241
  
• Hongying Meng, John Shawe-Taylor, Sándor Szedmák, Jason D. R. Farquhar:
  Support Vector Machine to Synthesise Kernels. 242-255
  
• Bram Vanschoenwinkel, Bernard Manderick:
  Appropriate Kernel Functions for Support Vector Machine Learning with Sequences of Symbolic Data. 256-280
  
• Bo Wang, D. M. Titterington:
  Variational Bayes Estimation of Mixing Coefficients. 281-295
  
• Joab Winkler:
  A Comparison of Condition Numbers for the Full Rank Least Squares Problem. 296-318
  
• Yaoyong Li, Kalina Bontcheva, Hamish Cunningham:
  SVM Based Learning System for Information Extraction. 319-339