Machine Learning and Knowledge Discovery in Databases (häftad)
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Format
Häftad (Paperback / softback)
Språk
Engelska
Antal sidor
691
Utgivningsdatum
2013-09-12
Upplaga
2013 ed.
Förlag
Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Medarbetare
Blockeel, Hendrik (ed.), Kersting, Kristian (ed.), Nijssen, Siegfried (ed.), Zeleznÿ, Filip (ed.)
Illustrationer
190 Illustrations, black and white; XLVI, 691 p. 190 illus.
Volymtitel
Part III
Dimensioner
235 x 153 x 41 mm
Vikt
1099 g
Antal komponenter
1
Komponenter
1 Paperback / softback
ISBN
9783642409936

Machine Learning and Knowledge Discovery in Databases

European Conference, ECML PKDD 2013, Prague, Czech Republic, September 23-27, 2013, Proceedings, Part III

av Hendrik Blockeel, Kristian Kersting, Siegfried Nijssen, Filip Elezn
Häftad,  Engelska, 2013-09-12
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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; and medical applications.
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Fler böcker av författarna

Hendrik Blockeel, Kristian Kersting, Siegfried Nijssen, Filip Elezn

Innehållsförteckning

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.

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