Deterministic and Statistical Methods in Machine Learning

Keyphrases

Publications

volume 3635, 2005

Deterministic and Statistical Methods in Machine Learning, First International Workshop, Sheffield, UK, September 7-10, 2004, Revised Lectures Deterministic and Statistical Methods in Machine Learning 3635 (2005)

2004

Bram Vanschoenwinkel, Bernard Manderick
Appropriate Kernel Functions for Support Vector Machine Learning with Sequences of Symbolic Data. Deterministic and Statistical Methods in Machine Learning (2004)
Joab R. Winkler
A Comparison of Condition Numbers for the Full Rank Least Squares Problem. Deterministic and Statistical Methods in Machine Learning (2004)
Neil D. Lawrence, John C. Platt, Michael I. Jordan
Extensions of the Informative Vector Machine. Deterministic and Statistical Methods in Machine Learning (2004)
Jonathan Goldstein, John C. Platt, Christopher J. C. Burges
Redundant Bit Vectors for Quickly Searching High-Dimensional Regions. Deterministic and Statistical Methods in Machine Learning (2004)
Stephen J. Roberts, Rizwan Choudrey
Bayesian Independent Component Analysis with Prior Constraints: An Application in Biosignal Analysis. Deterministic and Statistical Methods in Machine Learning (2004)
Petra Kudová, Roman Neruda
Kernel Based Learning Methods: Regularization Networks and RBF Networks. Deterministic and Statistical Methods in Machine Learning (2004)
Tom Shorrock, David J. C. MacKay, Chris Ball
Efficient Communication by Breathing. Deterministic and Statistical Methods in Machine Learning (2004)
Christopher M. Bishop, Ilkay Ulusoy
Object Recognition via Local Patch Labelling. Deterministic and Statistical Methods in Machine Learning (2004)
Gavin C. Cawley, Nicola L. C. Talbot, Gareth J. Janacek, Michael W. Peck
Bayesian Kernel Learning Methods for Parametric Accelerated Life Survival Analysis. Deterministic and Statistical Methods in Machine Learning (2004)
Peter Sollich
Can Gaussian Process Regression Be Made Robust Against Model Mismatch? Deterministic and Statistical Methods in Machine Learning (2004)
Roderick Murray-Smith, Barak A. Pearlmutter
Transformations of Gaussian Process Priors. Deterministic and Statistical Methods in Machine Learning (2004)
Dharmesh M. Maniyar, Ian T. Nabney
Guiding Local Regression Using Visualisation. Deterministic and Statistical Methods in Machine Learning (2004)
Hongying Meng, John Shawe-Taylor, Sándor Szedmák, Jason D. R. Farquhar
Support Vector Machine to Synthesise Kernels. Deterministic and Statistical Methods in Machine Learning (2004)
Samy Bengio, Hervé Bourlard
Multi Channel Sequence Processing. Deterministic and Statistical Methods in Machine Learning (2004)
Jeremy Rogers, Steve R. Gunn
Ensemble Algorithms for Feature Selection. Deterministic and Statistical Methods in Machine Learning (2004)
Yi Sun, Mark Robinson, Rod Adams, Paul Kaye, Alistair G. Rust, Neil Davey
Integrating Binding Site Predictions Using Non-linear Classification Methods. Deterministic and Statistical Methods in Machine Learning (2004)
Peter Sollich, Christopher K. I. Williams
Understanding Gaussian Process Regression Using the Equivalent Kernel. Deterministic and Statistical Methods in Machine Learning (2004)
Yaoyong Li, Kalina Bontcheva, Hamish Cunningham
SVM Based Learning System for Information Extraction. Deterministic and Statistical Methods in Machine Learning (2004)
Bo Wang, D. M. Titterington
Variational Bayes Estimation of Mixing Coefficients. Deterministic and Statistical Methods in Machine Learning (2004)