9783540466499-3540466495-Algorithmic Learning Theory: 17th International Conference, ALT 2006, Barcelona, Spain, October 7-10, 2006, Proceedings (Lecture Notes in Computer Science, 4264)

Algorithmic Learning Theory: 17th International Conference, ALT 2006, Barcelona, Spain, October 7-10, 2006, Proceedings (Lecture Notes in Computer Science, 4264)

ISBN-13: 9783540466499
ISBN-10: 3540466495
Edition: 2006
Author: José L. Balcázar, Frank Stephan, Philip M. Long
Publication date: 2006
Publisher: Springer
Format: Paperback 406 pages
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Book details

ISBN-13: 9783540466499
ISBN-10: 3540466495
Edition: 2006
Author: José L. Balcázar, Frank Stephan, Philip M. Long
Publication date: 2006
Publisher: Springer
Format: Paperback 406 pages

Summary

Algorithmic Learning Theory: 17th International Conference, ALT 2006, Barcelona, Spain, October 7-10, 2006, Proceedings (Lecture Notes in Computer Science, 4264) (ISBN-13: 9783540466499 and ISBN-10: 3540466495), written by authors José L. Balcázar, Frank Stephan, Philip M. Long, was published by Springer in 2006. With an overall rating of 4.4 stars, it's a notable title among other AI & Machine Learning (Algorithms, Programming, Software, Speech & Audio Processing, Digital Audio, Video & Photography , Computer Science) books. You can easily purchase or rent Algorithmic Learning Theory: 17th International Conference, ALT 2006, Barcelona, Spain, October 7-10, 2006, Proceedings (Lecture Notes in Computer Science, 4264) (Paperback) from BooksRun, along with many other new and used AI & Machine Learning books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.3.

Description

This book constitutes the refereed proceedings of the 17th International Conference on Algorithmic Learning Theory, ALT 2006, held in Barcelona, Spain in October 2006, colocated with the 9th International Conference on Discovery Science, DS 2006. The 24 revised full papers presented together with the abstracts of five invited papers were carefully reviewed and selected from 53 submissions. The papers are dedicated to the theoretical foundations of machine learning.
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