000 04205nam a22006255i 4500
001 978-3-642-40991-2
003 DE-He213
005 20200421112037.0
007 cr nn 008mamaa
008 130828s2013 gw | s |||| 0|eng d
020 _a9783642409912
_9978-3-642-40991-2
024 7 _a10.1007/978-3-642-40991-2
_2doi
050 4 _aQA76.9.D343
072 7 _aUNF
_2bicssc
072 7 _aUYQE
_2bicssc
072 7 _aCOM021030
_2bisacsh
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 II /
_cedited by Hendrik Blockeel, Kristian Kersting, Siegfried Nijssen, Filip Železn�y.
264 1 _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
347 _atext file
_bPDF
_2rda
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.
650 0 _aComputer science
_xMathematics.
650 0 _aMathematical statistics.
650 0 _aData mining.
650 0 _aInformation storage and retrieval.
650 0 _aArtificial intelligence.
650 0 _aPattern recognition.
650 1 4 _aComputer Science.
650 2 4 _aData Mining and Knowledge Discovery.
650 2 4 _aArtificial Intelligence (incl. Robotics).
650 2 4 _aPattern 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.
700 1 _aKersting, Kristian.
_eeditor.
700 1 _aNijssen, Siegfried.
_eeditor.
700 1 _aŽelezn�y, Filip.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783642409905
830 0 _aLecture Notes in Computer Science,
_x0302-9743 ;
_v8189
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-642-40991-2
912 _aZDB-2-SCS
912 _aZDB-2-LNC
942 _cEBK
999 _c56424
_d56424