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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 /

Collection : Lecture Notes in Computer Science, 0302-9743 ; . 8188 Détails physiques : LIV, 691 p. 198 illus. online resource. ISBN :9783642409882.
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Exemplaires : http://dx.doi.org/10.1007/978-3-642-40988-2

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.

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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