Machine Learning: ECML 2000: 11th European Conference on Machine Learning Barcelona, Catalonia, Spain May, 31 - June 2, 2000 Proceedings (Lecture Notes . / Lecture Notes in Artificial Intelligence)

Mantaras, Ramon Lopez de

ISBN 10: 3540676023 / ISBN 13: 9783540676027

Published by Springer, 2000

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Bibliographic Details

• Title: Machine Learning: ECML 2000: 11th European Conference on Machine Learning Barcelona, Catalonia, Spain May, 31 - June 2, 2000 Proceedings (Lecture Notes . / Lecture Notes in Artificial Intelligence)
• Publisher: Springer
• Publication Date: 2000
• Language: English
• ISBN 10: 3540676023
• ISBN 13: 9783540676027
• Binding: Paperback
• Condition: Like New
• Book Type: book

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Synopsis

The biennial European Conference on Machine Learning (ECML) series is intended to provide an international forum for the discussion of the latest high quality research results in machine learning and is the major European scienti?c event in the ?eld. The eleventh conference (ECML 2000) held in Barcelona, Catalonia, Spain from May 31 to June 2, 2000, has continued this tradition by attracting high quality papers from around the world. Scientists from 21 countries submitted 100 papers to ECML 2000, from which 20 were selected for long oral presentations and 23 for short oral presentations. This selection was based on the recommendations of at least two reviewers for each submitted paper. It is worth noticing that the number of papers reporting applications of machine learning has increased in comparison to past ECML conferences. We believe this fact shows the growing maturity of the ?eld. This volume contains the 43 accepted papers as well as the invited talks by Katharina Morik from theUniversity of Dortmund and Pedro Domingos from the University of Washington at Seattle. In addition, three workshops were jointly organized by ECML 2000 and the European Network of Excellence - net: “Dealing with Structured Data in Machine Learning and Statistics W- stites”, “Machine Learning in the New Information Age” , and “Meta-Learning: Building Automatic Advice Strategies for Model Selection and Method Com- nation”.