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024 7 _a10.1007/978-3-642-40988-2
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082 0 4 _a006.312
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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 I /
_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 _aLIV, 691 p. 198 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
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490 1 _aLecture Notes in Artificial Intelligence,
_x2945-9141 ;
_v8188
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; medical applications; nectar track; demo track.
650 0 _aData mining.
_93907
650 0 _aArtificial intelligence.
_93407
650 0 _aPattern recognition systems.
_93953
650 0 _aComputer science
_xMathematics.
_93866
650 0 _aDiscrete mathematics.
_912873
650 0 _aMathematical statistics.
_99597
650 0 _aInformation storage and retrieval systems.
_922213
650 1 4 _aData Mining and Knowledge Discovery.
_9138564
650 2 4 _aArtificial Intelligence.
_93407
650 2 4 _aAutomated Pattern Recognition.
_931568
650 2 4 _aDiscrete Mathematics in Computer Science.
_931837
650 2 4 _aProbability and Statistics in Computer Science.
_931857
650 2 4 _aInformation Storage and Retrieval.
_923927
700 1 _aBlockeel, Hendrik.
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700 1 _aKersting, Kristian.
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700 1 _aNijssen, Siegfried.
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700 1 _aŽelezný, Filip.
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_9138568
710 2 _aSpringerLink (Online service)
_9138569
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
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776 0 8 _iPrinted edition:
_z9783642409899
830 0 _aLecture Notes in Artificial Intelligence,
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_9138570
856 4 0 _uhttps://doi.org/10.1007/978-3-642-40988-2
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