Deterministic and Statistical Methods in Machine Learning

First International Workshop, Sheffield, UK, September 7-10, 2004. Revised Lectures

356 Seiten, Taschenbuch

Kurzbeschreibung des Verlags

Object Recognition via Local Patch Labelling.- Multi Channel Sequence Processing.- Bayesian Kernel Learning Methods for Parametric Accelerated Life Survival Analysis.- Extensions of the Informative Vector Machine.- Efficient Communication by Breathing.- Guiding Local Regression Using Visualisation.- Transformations of Gaussian Process Priors.- Kernel Based Learning Methods: Regularization Networks and RBF Networks.- Redundant Bit Vectors for Quickly Searching High-Dimensional Regions.- Bayesian Independent Component Analysis with Prior Constraints: An Application in Biosignal Analysis.- Ensemble Algorithms for Feature Selection.- Can Gaussian Process Regression Be Made Robust Against Model Mismatch?.- Understanding Gaussian Process Regression Using the Equivalent Kernel.- Integrating Binding Site Predictions Using Non-linear Classification Methods.- Support Vector Machine to Synthesise Kernels.- Appropriate Kernel Functions for Support Vector Machine Learning with Sequences of Symbolic Data.- Variational Bayes Estimation of Mixing Coefficients.- A Comparison of Condition Numbers for the Full Rank Least Squares Problem.- SVM Based Learning System for Information Extraction.

• Reihe: Lecture Notes in Computer Science
• Themen: Informatik und Informationstechnologie Datenbanken / Datenmanagement Data Warehousing
• ISBN: 9783540290735
• Sprache: Englisch
• Erscheinungsdatum: 11.10.2005
• Größe: 235 x 155 mm
• Verlag: Springer
• Herausgegeben von: Joab Winkler, Mahesan Niranjan, Neil Lawrence