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Deterministic and Statistical Methods in Machine Learning

  • Kartonierter Einband
  • 356 Seiten
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Machinelearningis arapidlymaturing?eldthataims toprovidepracticalme- ods for data discovery, categorization and modelling. The She... Weiterlesen
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Machinelearningis arapidlymaturing?eldthataims toprovidepracticalme- ods for data discovery, categorization and modelling. The She?eld Machine Learning Workshop, which was held 7 10 September 2004, brought together some of the leading international researchers in the ?eld for a series of talks and posters that represented new developments in machine learning and numerical methods. The workshop was sponsored by the Engineering and Physical Sciences - search Council (EPSRC) and the London Mathematical Society (LMS) through the MathFIT program,whose aim is the encouragementof new interdisciplinary research.AdditionalfundingwasprovidedbythePASCALEuropeanFramework 6 Network of Excellence and the University of She?eld. It was the commitment of these funding bodies that enabled the workshop to have a strong program of invited speakers,and the organizerswish to thank these funding bodies for their ?nancial support. The particular focus for interactions at the workshop was - vanced Research Methods in Machine Learning and Statistical Signal Processing. These proceedings contain work that was presented at the workshop, and ideas that were developed through, or inspired by, attendance at the workshop. The proceedings re?ect this mixture and illustrate the diversity of applications and theoretical work in machine learning. We would like to thank the presenters and attendees at the workshop for the excellent quality of presentation and discussion during the oral and poster sessions. We are also grateful to Gillian Callaghan for her support in the orga- zation of the workshop, and ?nally we wish to thank the anonymous reviewers for their help in compiling the proceedings.


This book consitutes the refereed proceedings of the First International Workshop on Machine Learning held in Sheffield, UK, in September 2004. The 19 revised full papers presented were carefully reviewed and selected for inclusion in the book. They address all current issues in the rapidly maturing field of machine learning that aims to provide practical methods for data discovery, categorisation and modelling. The particular focus of the workshop was advanced research methods in machine learning and statistical signal processing.

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.


Titel: Deterministic and Statistical Methods in Machine Learning
Untertitel: First International Workshop, Sheffield, UK, September 7-10, 2004. Revised Lectures
EAN: 9783540290735
ISBN: 3540290737
Format: Kartonierter Einband
Herausgeber: Springer Berlin Heidelberg
Genre: Informatik
Anzahl Seiten: 356
Gewicht: 605g
Größe: H235mm x B155mm x T21mm
Jahr: 2005
Untertitel: Englisch
Auflage: 2005

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