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Deterministic and statistical methods in machine learning : first international workshop, Sheffield, UK, September 7-10, 2004 : revised lectures

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Cover of 'Deterministic and statistical methods in machine learning : first international workshop, Sheffield, UK, September 7-10, 2004 : revised lectures'

Table of Contents

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    Book Overview
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    Chapter 1 Object Recognition via Local Patch Labelling
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    Chapter 2 Multi Channel Sequence Processing
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    Chapter 3 Bayesian Kernel Learning Methods for Parametric Accelerated Life Survival Analysis
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    Chapter 4 Extensions of the Informative Vector Machine
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    Chapter 5 Efficient Communication by Breathing
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    Chapter 6 Guiding Local Regression Using Visualisation
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    Chapter 7 Transformations of Gaussian Process Priors
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    Chapter 8 Kernel Based Learning Methods: Regularization Networks and RBF Networks
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    Chapter 9 Redundant Bit Vectors for Quickly Searching High-Dimensional Regions
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    Chapter 10 Bayesian Independent Component Analysis with Prior Constraints: An Application in Biosignal Analysis
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    Chapter 11 Ensemble Algorithms for Feature Selection
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    Chapter 12 Can Gaussian Process Regression Be Made Robust Against Model Mismatch?
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    Chapter 13 Understanding Gaussian Process Regression Using the Equivalent Kernel
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    Chapter 14 Integrating Binding Site Predictions Using Non-linear Classification Methods
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    Chapter 15 Support Vector Machine to Synthesise Kernels
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    Chapter 16 Appropriate Kernel Functions for Support Vector Machine Learning with Sequences of Symbolic Data
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    Chapter 17 Variational Bayes Estimation of Mixing Coefficients
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    Chapter 18 A Comparison of Condition Numbers for the Full Rank Least Squares Problem
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    Chapter 19 SVM Based Learning System for Information Extraction
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Title
Deterministic and statistical methods in machine learning : first international workshop, Sheffield, UK, September 7-10, 2004 : revised lectures
Published by
Springer, January 2005
DOI 10.1007/11559887
ISBNs
978-3-54-029073-5, 978-3-54-031728-9
Authors

Winkler, Joab, Niranjan, Mahesan, Lawrence, Neil

Editors

Joab Winkler, Mahesan Niranjan, Neil Lawrence

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X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 4%
Unknown 22 96%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 17%
Researcher 4 17%
Lecturer > Senior Lecturer 2 9%
Student > Bachelor 2 9%
Other 1 4%
Other 4 17%
Unknown 6 26%
Readers by discipline Count As %
Computer Science 6 26%
Agricultural and Biological Sciences 3 13%
Physics and Astronomy 2 9%
Neuroscience 2 9%
Biochemistry, Genetics and Molecular Biology 1 4%
Other 3 13%
Unknown 6 26%