000 04225nam a22006255i 4500
001 978-3-642-40988-2
003 DE-He213
005 20200420221258.0
007 cr nn 008mamaa
008 130828s2013 gw | s |||| 0|eng d
020 _a9783642409882
_9978-3-642-40988-2
024 7 _a10.1007/978-3-642-40988-2
_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 I /
_cedited by Hendrik Blockeel, Kristian Kersting, Siegfried Nijssen, Filip Železn�y.
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
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aLecture Notes in Computer Science,
_x0302-9743 ;
_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 _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:
_z9783642409875
830 0 _aLecture Notes in Computer Science,
_x0302-9743 ;
_v8188
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-642-40988-2
912 _aZDB-2-SCS
912 _aZDB-2-LNC
942 _cEBK
999 _c53056
_d53056