MARC record from Internet Archive

LEADER: 13247cam 2200853Ka 4500
001 ocn810326912
003 OCoLC
005 20210716044951.0
008 120920s2012 gw a ob 101 0 eng d
006 m o d
007 cr cnu---unuuu
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019 $a848105571
020 $a9783642334863$q(electronic bk.)
020 $a3642334865$q(electronic bk.)
020 $z3642334857$q(print)
020 $z9783642334856$q(print)
024 7 $a10.1007/978-3-642-33486-3$2doi
035 $a(OCoLC)810326912$z(OCoLC)848105571
050 4 $aQ325.5$b.E26 2012eb
082 04 $a006.3/1$223
111 2 $aECML PKDD (Conference)$d(2012 :$cBristol, England)
245 10 $aMachine learning and knowledge discovery in databases.$nPart II :$bEuropean conference, ECML PKDD 2012, Bristol, UK, September 24-28, 2012, proceedings /$cPeter A. Flach, Tijl De Bie, Nello Cristianini (eds.).
246 3 $aECML PKDD 2012
260 $aBerlin ;$aNew York :$bSpringer,$c©2012.
300 $a1 online resource (xxvi, 867 pages) :$billustrations
336 $atext$btxt$2rdacontent
337 $acomputer$bc$2rdamedia
338 $aonline resource$bcr$2rdacarrier
490 1 $aLecture notes in artificial intelligence ;$v7524
490 1 $aLNCS sublibrary. SL 7, Artificial intelligence
504 $aIncludes bibliographical references and index.
505 00 $tAUDIO: An Integrity Auditing Framework of Outlier-Mining-as-a-Service Systems /$rRuilin Liu, Hui (Wendy) Wang, Anna Monreale, Dino Pedreschi and Fosca Giannotti, et al. --$tDifferentially Private Projected Histograms: Construction and Use for Prediction /$rStaal A. Vinterbo --$tFairness-Aware Classifier with Prejudice Remover Regularizer /$rToshihiro Kamishima, Shotaro Akaho, Hideki Asoh and Jun Sakuma --$tA Live Comparison of Methods for Personalized Article Recommendation at Forbes.com /$rEvan Kirshenbaum, George Forman and Michael Dugan --$tFast ALS-Based Tensor Factorization for Context-Aware Recommendation from Implicit Feedback /$rBalázs Hidasi and Domonkos Tikk --$tProbability Estimation for Multi-class Classification Based on Label Ranking /$rWeiwei Cheng and Eyke Hüllermeier --$tAdaptive Planning for Markov Decision Processes with Uncertain Transition Models via Incremental Feature Dependency Discovery /$rN. Kemal Ure, Alborz Geramifard, Girish Chowdhary and Jonathan P. How --$tAPRIL: Active Preference Learning-Based Reinforcement Learning /$rRiad Akrour, Marc Schoenauer and Michèle Sebag.
505 00 $tAutonomous Data-Driven Decision-Making in Smart Electricity Markets /$rMarkus Peters, Wolfgang Ketter, Maytal Saar-Tsechansky and John Collins --$tBayesian Nonparametric Inverse Reinforcement Learning /$rBernard Michini and Jonathan P. How --$tBootstrapping Monte Carlo Tree Search with an Imperfect Heuristic /$rTruong-Huy Dinh Nguyen, Wee-Sun Lee and Tze-Yun Leong --$tFast Reinforcement Learning with Large Action Sets Using Error-Correcting Output Codes for MDP Factorization /$rGabriel Dulac-Arnold, Ludovic Denoyer, Philippe Preux and Patrick Gallinari --$tLearning Policies for Battery Usage Optimization in Electric Vehicles /$rStefano Ermon, Yexiang Xue, Carla Gomes and Bart Selman --$tPolicy Iteration Based on a Learned Transition Model /$rVivek Ramavajjala and Charles Elkan --$tStructured Apprenticeship Learning /$rAbdeslam Boularias, Oliver Krömer and Jan Peters --$tA Bayesian Approach for Classification Rule Mining in Quantitative Databases /$rDominique Gay and Marc Boullé --$tA Bayesian Scoring Technique for Mining Predictive and Non-Spurious Rules /$rIyad Batal, Gregory Cooper and Milos Hauskrecht.
505 00 $tGeneric Pattern Trees for Exhaustive Exceptional Model Mining /$rFlorian Lemmerich, Martin Becker and Martin Atzmueller --$tBidirectional Semi-supervised Learning with Graphs /$rTomoharu Iwata and Kevin Duh --$tCoupled Bayesian Sets Algorithm for Semi-supervised Learning and Information Extraction /$rSaurabh Verma and Estevam R. Hruschka Jr. --$tGraph-Based Transduction with Confidence /$rMatan Orbach and Koby Crammer --$tMaximum Consistency Preferential Random Walks /$rDeguang Kong and Chris Ding --$tSemi-supervised Multi-label Classification /$rA Simultaneous Large-Margin, Subspace Learning Approach /$rYuhong Guo and Dale Schuurmans --$tMDL-Based Analysis of Time Series at Multiple Time-Scales /$rUgo Vespier, Arno Knobbe, Siegfried Nijssen and Joaquin Vanschoren --$tSeparable Approximate Optimization of Support Vector Machines for Distributed Sensing /$rSangkyun Lee, Marco Stolpe and Katharina Morik --$tUnsupervised Inference of Auditory Attention from Biosensors /$rMelih Kandemir, Arto Klami, Akos Vetek and Samuel Kaski --$tA Family of Feed-Forward Models for Protein Sequence Classification /$rSam Blasiak, Huzefa Rangwala and Kathryn B. Laskey.
505 00 $tGeneral Algorithms for Mining Closed Flexible Patterns under Various Equivalence Relations /$rTomohiro I, Yuki Enokuma, Hideo Bannai and Masayuki Takeda --$tSize Matters: Finding the Most Informative Set of Window Lengths /$rJefrey Lijffijt, Panagiotis Papapetrou and Kai Puolamäki --$tDiscovering Links among Social Networks /$rFrancesco Buccafurri, Gianluca Lax, Antonino Nocera and Domenico Ursino --$tEfficient Bi-objective Team Formation in Social Networks /$rMehdi Kargar, Aijun An and Morteza Zihayat --$tFeature-Enhanced Probabilistic Models for Diffusion Network Inference /$rLiaoruo Wang, Stefano Ermon and John E. Hopcroft --$tInfluence Spread in Large-Scale Social Networks -- A Belief Propagation Approach /$rHuy Nguyen and Rong Zheng --$tLocation Affiliation Networks: Bonding Social and Spatial Information /$rKonstantinos Pelechrinis and Prashant Krishnamurthy --$tOn Approximation of Real-World Influence Spread /$rYu Yang, Enhong Chen, Qi Liu, Biao Xiang and Tong Xu, et al. --$tOpinion Formation by Voter Model with Temporal Decay Dynamics /$rMasahiro Kimura, Kazumi Saito, Kouzou Ohara and Hiroshi Motoda.
505 00 $tViral Marketing for Product Cross-Sell through Social Networks /$rRamasuri Narayanam and Amit A. Nanavati --$tWhich Topic Will You Follow? /$rDeqing Yang, Yanghua Xiao, Bo Xu, Hanghang Tong and Wei Wang, et al. --$tInferring Geographic Coincidence in Ephemeral Social Networks /$rHonglei Zhuang, Alvin Chin, Sen Wu, Wei Wang and Xia Wang, et al. --$tPedestrian Quantity Estimation with Trajectory Patterns /$rThomas Liebig, Zhao Xu, Michael May and Stefan Wrobel --$tSocioscope: Spatio-temporal Signal Recovery from Social Media /$rJun-Ming Xu, Aniruddha Bhargava, Robert Nowak and Xiaojin Zhu --$tA Framework for Evaluating the Smoothness of Data-Mining Results /$rGaurav Misra, Behzad Golshan and Evimaria Terzi --$tActive Evaluation of Ranking Functions Based on Graded Relevance /$rChristoph Sawade, Steffen Bickel, Timo von Oertzen, Tobias Scheffer and Niels Landwehr --$tCommunity Trend Outlier Detection Using Soft Temporal Pattern Mining /$rManish Gupta, Jing Gao, Yizhou Sun and Jiawei Han --$tData Structures for Detecting Rare Variations in Time Series /$rCaio Valentim, Eduardo S. Laber and David Sotelo.
505 00 $tInvariant Time-Series Classification /$rJosif Grabocka, Alexandros Nanopoulos and Lars Schmidt-Thieme --$tLearning Bi-clustered Vector Autoregressive Models /$rTzu-Kuo Huang and Jeff Schneider --$tDiscriminative Factor Alignment across Heterogeneous Feature Space /$rFangwei Hu, Tianqi Chen, Nathan N. Liu, Qiang Yang and Yong Yu --$tLearning to Perceive Two-Dimensional Displays Using Probabilistic Grammars /$rNan Li, William W. Cohen and Kenneth R. Koedinger --$tTransfer Spectral Clustering /$rWenhao Jiang and Fu-lai Chung --$tAn Aspect-Lexicon Creation and Evaluation Tool for Sentiment Analysis Researchers /$rMus'ab Husaini, Ahmet Koçyiğit, Dilek Tapucu, Berrin Yanikoglu and Yücel Saygın --$tAssociation Rule Mining Following the Web Search Paradigm /$rRadek Škrabal, Milan Šimůnek, Stanislav Vojíř, Andrej Hazucha and Tomáš Marek, et al. --$tASV Monitor: Creating Comparability of Machine Learning Methods for Content Analysis /$rAndreas Niekler, Patrick Jähnichen and Gerhard Heyer --$tClowdFlows: A Cloud Based Scientific Workflow Platform /$rJanez Kranjc, Vid Podpečan and Nada Lavrač
505 00 $tExtracting Trajectories through an Efficient and Unifying Spatio-temporal Pattern Mining System /$rPhan Nhat Hai, Dino Ienco, Pascal Poncelet and Maguelonne Teisseire --$tKnowledge Discovery through Symbolic Regression with HeuristicLab /$rGabriel Kronberger, Stefan Wagner, Michael Kommenda, Andreas Beham and Andreas Scheibenpflug, et al. --$tOutRules: A Framework for Outlier Descriptions in Multiple Context Spaces /$rEmmanuel Müller, Fabian Keller, Sebastian Blanc and Klemens Böhm --$tScientific Workflow Management with ADAMS /$rPeter Reutemann and Joaquin Vanschoren --$tTopicExplorer: Exploring Document Collections with Topic Models /$rAlexander Hinneburg, Rico Preiss and René Schröder --$tVIKAMINE -- Open-Source Subgroup Discovery, Pattern Mining, and Analytics /$rMartin Atzmueller and Florian Lemmerich --$tLearning Submodular Functions /$rMaria-Florina Balcan and Nicholas J.A. Harvey --$tMatrix Factorization as Search /$rKristian Kersting, Christian Bauckhage, Christian Thurau and Mirwaes Wahabzada --$tMetal Binding in Proteins: Machine Learning Complements X-Ray Absorption Spectroscopy /$rMarco Lippi, Andrea Passerini, Marco Punta and Paolo Frasconi --$tModelling Input Varying Correlations between Multiple Responses /$rAndrew Gordon Wilson and Zoubin Ghahramani.
588 0 $aPrint version record.
520 $aThis two-volume set LNAI 7523 and LNAI 7524 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2012, held in Bristol, UK, in September 2012. The 105 revised research papers presented together with 5 invited talks were carefully reviewed and selected from 443 submissions. The final sections of the proceedings are devoted to Demo and Nectar papers. The Demo track includes 10 papers (from 19 submissions) and the Nectar track includes 4 papers (from 14 submissions). The papers grouped in topical sections on association rules and frequent patterns; Bayesian learning and graphical models; classification; dimensionality reduction, feature selection and extraction; distance-based methods and kernels; ensemble methods; graph and tree mining; large-scale, distributed and parallel mining and learning; multi-relational mining and learning; multi-task learning; natural language processing; online learning and data streams; privacy and security; rankings and recommendations; reinforcement learning and planning; rule mining and subgroup discovery; semi-supervised and transductive learning; sensor data; sequence and string mining; social network mining; spatial and geographical data mining; statistical methods and evaluation; time series and temporal data mining; and transfer learning.
650 0 $aMachine learning$vCongresses.
650 0 $aData mining$vCongresses.
650 7 $aInformatique.$2eclas
650 7 $aData mining.$2fast$0(OCoLC)fst00887946
650 7 $aMachine learning.$2fast$0(OCoLC)fst01004795
655 0 $aElectronic books.
655 4 $aElectronic books.
655 7 $aConference papers and proceedings.$2fast$0(OCoLC)fst01423772
700 1 $aFlach, Peter A.
700 1 $aDe Bie, Tijl.
700 1 $aCristianini, Nello.
776 08 $iPrint version:$tMachine learning and knowledge discovery in databases.$d[S.l.] : Springer, 2012$z3642334598$w(OCoLC)807033592
830 0 $aLecture notes in computer science.$pLecture notes in artificial intelligence ;$v7524.
830 0 $aLNCS sublibrary.$nSL 7,$pArtificial intelligence.
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