Machine Learning and Knowledge Discovery in Databases European Conference, ECML PKDD 2013, Prague, Czech Republic, September 23-27, 2013, Proceedings, Part I /

Machine Learning and Knowledge Discovery in Databases European Conference, ECML PKDD 2013, Prague, Czech Republic, September 23-27, 2013, Proceedings, Part I /

This three-volume set LNAI 8188, 8189 and 8190 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2013, held in Prague, Czech Republic, in September 2013. The 111 revised research papers presented together with 5 invite...

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Bibliographic Details
Published in:Springer eBooks
Corporate Author: SpringerLink (Online service)
Other Authors: Blockeel, Hendrik (Editor), Kersting, Kristian (Editor), Nijssen, Siegfried (Editor), Železný, Filip (Editor)
Format: eBook
Language:English
Published: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013.
Series:Lecture Notes in Computer Science,
Subjects:
Computer Science.
Computational complexity.
Data mining.
Information storage and retrieval systems.
Artificial intelligence.
Optical pattern recognition.
Data Mining and Knowledge Discovery.
Artificial Intelligence (incl. Robotics).
Pattern Recognition.
Discrete Mathematics in Computer Science.
Probability and Statistics in Computer Science.
Information Storage and Retrieval.
Online Access:http://dx.doi.org/10.1007/978-3-642-40988-2
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Description
Summary:This three-volume set LNAI 8188, 8189 and 8190 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2013, held in Prague, Czech Republic, in September 2013. The 111 revised research papers presented together with 5 invited talks were carefully reviewed and selected from 447 submissions. The papers are organized in topical sections on reinforcement learning; Markov decision processes; active learning and optimization; learning from sequences; time series and spatio-temporal data; data streams; graphs and networks; social network analysis; natural language processing and information extraction; ranking and recommender systems; matrix and tensor analysis; structured output prediction, multi-label and multi-task learning; transfer learning; bayesian learning; graphical models; nearest-neighbor methods; ensembles; statistical learning; semi-supervised learning; unsupervised learning; subgroup discovery, outlier detection and anomaly detection; privacy and security; evaluation; applications; medical applications; nectar track; demo track.
Physical Description:LIV, 691 p. 198 illus. online resource.
ISBN:9783642409882
ISSN:0302-9743 ;

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