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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
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 invite...
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| Auteurs principaux : | , , |
|---|---|
| Format : | Livre |
| Langue : | anglais |
| Titre complet : | 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. |
| Publié : |
Berlin, Heidelberg :
Springer Berlin Heidelberg
, 2013 Cham : Springer Nature |
| Collection : | Lecture Notes in Artificial Intelligence ; 8188 |
| Accès en ligne : |
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| Condition d'utilisation et de reproduction : | Conditions particulières de réutilisation pour les bénéficiaires des licences nationales : chttps://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 |
| Sujets : | |
| Documents associés : | Autre format:
Machine Learning and Knowledge Discovery in Databases Autre format: Machine Learning and Knowledge Discovery in Databases |
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| 225 | 0 | |a Lecture Notes in Artificial Intelligence |x 2945-9141 |v 8188 | |
| 330 | |a 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. | ||
| 359 | 1 | |a 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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