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

Gespeichert in:

Personen und Körperschaften:	Blockeel, Hendrik (VerfasserIn), Kersting, Kristian (HerausgeberIn), Nijssen, Siegfried (HerausgeberIn), Železný, Filip (HerausgeberIn)
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:	Computational complexity Optical pattern recognition Computer Science Computer science Data mining Information storage and retrieval systems Artificial intelligence Discrete mathematics. Mathematical statistics. Pattern recognition systems. Konferenzschrift
Druckausg.:	Machine learning and knowledge discovery in databases ; 1, Berlin : Springer, 2013, LIV, 691 S.
Quelle:	Verbunddaten SWB
Zugangsinformationen:	Elektronischer Volltext - Campuslizenz

Details
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
Beschreibung:	Literaturangaben
Umfang:	Online-Ressource (LIV, 691 p. 198 illus, online resource)
ISBN:	9783642409882
DOI:	10.1007/978-3-642-40988-2