Machine Learning and Knowledge Discovery in Databases [[electronic resource] ] : 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

• Pubblicazione: Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2013
• Edizione: 1st ed. 2013.
• Descrizione fisica: 1 online resource (LIV, 691 p. 198 illus.)
• Disciplina: 006.31
• Soggetto topico: Data mining; Artificial intelligence; Pattern recognition; Computer science—Mathematics; Mathematical statistics; Information storage and retrieval; Data Mining and Knowledge Discovery; Artificial Intelligence; Pattern Recognition; Discrete Mathematics in Computer Science; Probability and Statistics in Computer Science; Information Storage and Retrieval
• Persona (resp. second.): BlockeelHendrik; KerstingKristian; NijssenSiegfried; ŽeleznýFilip
• Note generali: Bibliographic Level Mode of Issuance: Monograph
• Nota di contenuto: 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.
• Sommario/riassunto: 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.
• Titolo autorizzato: Machine Learning and Knowledge Discovery in Databases
• ISBN: 3-642-40988-1
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 996466041203316
• Lo trovi qui: Univ. di Salerno
• Serie: Lecture Notes in Artificial Intelligence ; ; 8188