Deterministic and Statistical Methods in Machine Learning First International Workshop, Sheffield, UK, September 7-10, 2004. Revised Lectures / [electronic resource] :
edited by Joab Winkler, Mahesan Niranjan, Neil Lawrence.
- VIII, 341 p. Also available online. online resource.
- Lecture Notes in Computer Science, 3635 0302-9743 ; .
- Lecture Notes in Computer Science, 3635 .
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.
ZDB-2-SCS ZDB-2-LNC
9783540317289
10.1007/11559887 doi
Computer science. Database management. Information storage and retrieval systems. Artificial intelligence. Computer vision. Optical pattern recognition. Computer Science. Artificial Intelligence (incl. Robotics). Mathematical Logic and Formal Languages. Database Management. Information Storage and Retrieval. Image Processing and Computer Vision. Pattern Recognition.