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Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2013, Prague, Czech Republic, September 23-27, 2013, Proceedings, Part I
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Titel: | Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2013, Prague, Czech Republic, September 23-27, 2013, Proceedings, Part I/ edited by Hendrik Blockeel, Kristian Kersting, Siegfried Nijssen, Filip Železný |
Format: | E-Book Konferenzbericht |
Sprache: | Englisch |
veröffentlicht: |
Berlin, Heidelberg
Springer
2013
|
Gesamtaufnahme: |
SpringerLink Lecture notes in computer science ; 8188 |
Schlagwörter: | |
Druckausg.: | Machine learning and knowledge discovery in databases ; 1, Berlin : Springer, 2013, LIV, 691 S. |
Quelle: | Verbunddaten SWB |
Zugangsinformationen: | Elektronischer Volltext - Campuslizenz |
Zusammenfassung: | 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 |
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Beschreibung: | Literaturangaben |
Umfang: | Online-Ressource (LIV, 691 p. 198 illus, online resource) |
ISBN: |
9783642409882
|
DOI: | 10.1007/978-3-642-40988-2 |