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024 7 _a10.1007/978-3-642-40994-3
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072 7 _aUNF
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082 0 4 _a006.312
_223
245 1 0 _aMachine Learning and Knowledge Discovery in Databases
_h[electronic resource] :
_bEuropean Conference, ECML PKDD 2013, Prague, Czech Republic, September 23-27, 2013, Proceedings, Part III /
_cedited by Hendrik Blockeel, Kristian Kersting, Siegfried Nijssen, Filip Železný.
250 _a1st ed. 2013.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2013.
300 _aXLVI, 691 p. 190 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aLecture Notes in Artificial Intelligence,
_x2945-9141 ;
_v8190
505 0 _aReinforcement 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.
520 _aThis 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; and medical applications.
650 0 _aData mining.
650 0 _aArtificial intelligence.
650 0 _aPattern recognition systems.
650 0 _aComputer science
_xMathematics.
650 0 _aDiscrete mathematics.
650 0 _aMathematical statistics.
650 0 _aInformation storage and retrieval systems.
650 1 4 _aData Mining and Knowledge Discovery.
650 2 4 _aArtificial Intelligence.
650 2 4 _aAutomated Pattern Recognition.
650 2 4 _aDiscrete Mathematics in Computer Science.
650 2 4 _aProbability and Statistics in Computer Science.
650 2 4 _aInformation Storage and Retrieval.
700 1 _aBlockeel, Hendrik.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aKersting, Kristian.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aNijssen, Siegfried.
_eeditor.
_4edt
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700 1 _aŽelezný, Filip.
_eeditor.
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710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783642409936
776 0 8 _iPrinted edition:
_z9783642409950
830 0 _aLecture Notes in Artificial Intelligence,
_x2945-9141 ;
_v8190
856 4 0 _uhttps://doi.org/10.1007/978-3-642-40994-3
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