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020 _a9783642409912
_9978-3-642-40991-2
024 7 _a10.1007/978-3-642-40991-2
_2doi
035 _ato000485352
040 _aSpringer
_cSpringer
_dRU-ToGU
050 4 _aQA76.9.D343
072 7 _aUNF
_2bicssc
072 7 _aUYQE
_2bicssc
072 7 _aCOM021030
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082 0 4 _a006.312
_223
100 1 _aBlockeel, Hendrik.
_eeditor.
_9330368
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 II /
_cedited by Hendrik Blockeel, Kristian Kersting, Siegfried Nijssen, Filip Železný.
260 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2013.
300 _aXLIV, 693 p. 160 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
490 1 _aLecture Notes in Computer Science,
_x0302-9743 ;
_v8189
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 _aComputer Science.
_9155490
650 0 _aComputational complexity.
_9304814
650 0 _aData mining.
_9306371
650 0 _aInformation storage and retrieval systems.
_9137013
650 0 _aArtificial intelligence.
_9274099
650 0 _aOptical pattern recognition.
_9304126
650 1 4 _aComputer Science.
_9155490
650 2 4 _aData Mining and Knowledge Discovery.
_9306372
650 2 4 _aArtificial Intelligence (incl. Robotics).
_9274102
650 2 4 _aPattern Recognition.
_9304129
650 2 4 _aDiscrete Mathematics in Computer Science.
_9304816
650 2 4 _aProbability and Statistics in Computer Science.
_9304554
650 2 4 _aInformation Storage and Retrieval.
_9303027
700 1 _aKersting, Kristian.
_eeditor.
_9328694
700 1 _aNijssen, Siegfried.
_eeditor.
_9415906
700 1 _aŽelezný, Filip.
_eeditor.
_9415907
710 2 _aSpringerLink (Online service)
_9143950
773 0 _tSpringer eBooks
830 0 _aLecture Notes in Computer Science,
_9279505
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-642-40991-2
912 _aZDB-2-SCS
912 _aZDB-2-LNC
999 _c357565