LEADER 08304nam 22007575 450 001 996466463803316 005 20200703201537.0 010 $a3-030-10928-3 024 7 $a10.1007/978-3-030-10928-8 035 $a(CKB)4100000007522527 035 $a(DE-He213)978-3-030-10928-8 035 $a(MiAaPQ)EBC5925326 035 $a(PPN)233799524 035 $a(EXLCZ)994100000007522527 100 $a20190122d2019 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMachine Learning and Knowledge Discovery in Databases$b[electronic resource] $eEuropean Conference, ECML PKDD 2018, Dublin, Ireland, September 10?14, 2018, Proceedings, Part II /$fedited by Michele Berlingerio, Francesco Bonchi, Thomas Gärtner, Neil Hurley, Georgiana Ifrim 205 $a1st ed. 2019. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2019. 215 $a1 online resource (XXX, 866 p. 463 illus., 192 illus. in color.) 225 1 $aLecture Notes in Artificial Intelligence ;$v11052 311 $a3-030-10927-5 327 $aGraphs -- Temporally Evolving Community Detection and Prediction in Content-Centric Networks -- Local Topological Data Analysis to Uncover the Global Structure of Data Approaching Graph-Structured Topologies -- Similarity Modeling on Heterogeneous Networks via Automatic Path Discovery -- Dynamic hierarchies in temporal directed networks -- Risk-Averse Matchings over Uncertain Graph Databases -- Discovering Urban Travel Demands through Dynamic Zone Correlation in Location-Based Social Networks -- Social-Affiliation Networks: Patterns and the SOAR Model -- ONE-M: Modeling the Co-evolution of Opinions and Network Connections -- Think before You Discard: Accurate Triangle Counting in Graph Streams with Deletions -- Semi-Supervised Blockmodelling with Pairwise Guidance -- Kernel Methods -- Large-scale Nonlinear Variable Selection via Kernel Random Features -- Fast and Provably Effective Multi-view Classification with Landmark-based SVM -- Nyström-SGD: Fast Learning of Kernel-Classifiers with Conditioned Stochastic Gradient Descent -- Learning Paradigms -- Hyperparameter Learning for Conditional Kernel Mean Embeddings with Rademacher Complexity Bounds -- Deep Learning Architecture Search by Neuro-Cell-based Evolution with Function-Preserving Mutations -- VC-Dimension Based Generalization Bounds for Relational Learning -- Robust Super-Level Set Estimation using Gaussian Processes -- Robust Super-Level Set Estimation using Gaussian Processes -- Scalable Nonlinear AUC Maximization Methods -- Matrix and Tensor Analysis -- Lambert Matrix Factorization -- Identifying and Alleviating Concept Drift in Streaming Tensor Decomposition -- MASAGA: A Linearly-Convergent Stochastic First-Order Method for Optimization on Manifolds -- Block CUR: Decomposing Matrices using Groups of Columns -- Online and Active Learning -- SpectralLeader: Online Spectral Learning for Single Topic Models -- Online Learning of Weighted Relational Rules for Complex Event Recognition -- Toward Interpretable Deep Reinforcement Learning with Linear Model U-Trees -- Online Feature Selection by Adaptive Sub-gradient Methods -- Frame-based Optimal Design -- Hierarchical Active Learning with Proportion Feedback on Regions -- Pattern and Sequence Mining -- An Efficient Algorithm for Computing Entropic Measures of Feature Subsets -- Anytime Subgroup Discovery in Numerical Domains with Guarantees -- Discovering Spatio-Temporal Latent Influence in Geographical Attention Dynamics -- Mining Periodic Patterns with a MDL Criterion -- Revisiting Conditional Functional Dependency Discovery: Splitting the ?C" from the ?FD" -- Sqn2Vec: Learning Sequence Representation via Sequential Patterns with a Gap Constraint -- Mining Tree Patterns with Partially Injective Homomorphisms -- Probabilistic Models and Statistical Methods -- Variational Bayes for Mixture Models with Censored Data -- Exploration Enhanced Expected Improvement for Bayesian Optimization -- A Left-to-right Algorithm for Likelihood Estimation in Gamma-Poisson Factor Analysis -- Causal Inference on Multivariate and Mixed-Type Data -- Recommender Systems -- POLAR: Attention-based CNN for One-shot Personalized Article Recommendation -- Learning Multi-granularity Dynamic Network Representations for Social Recommendation -- GeoDCF: Deep Collaborative Filtering with Multifaceted Contextual Information in Location-based Social Networks -- Personalized Thread Recommendation for MOOC Discussion Forums -- Inferring Continuous Latent Preference on Transition Intervals for Next Point-of-Interest Recommendation -- Transfer Learning -- Feature Selection for Unsupervised Domain Adaptation using Optimal Transport -- Towards more Reliable Transfer Learning -- Differentially Private Hypothesis Transfer Learning -- Information-theoretic Transfer Learning framework for Bayesian Optimisation -- A Unified Framework for Domain Adaptation using Metric Learning on Manifolds. 330 $aThe three volume proceedings LNAI 11051 ? 11053 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2018, held in Dublin, Ireland, in September 2018. The total of 131 regular papers presented in part I and part II was carefully reviewed and selected from 535 submissions; there are 52 papers in the applied data science, nectar and demo track. The contributions were organized in topical sections named as follows: Part I: adversarial learning; anomaly and outlier detection; applications; classification; clustering and unsupervised learning; deep learningensemble methods; and evaluation. Part II: graphs; kernel methods; learning paradigms; matrix and tensor analysis; online and active learning; pattern and sequence mining; probabilistic models and statistical methods; recommender systems; and transfer learning. Part III: ADS data science applications; ADS e-commerce; ADS engineering and design; ADS financial and security; ADS health; ADS sensing and positioning; nectar track; and demo track. 410 0$aLecture Notes in Artificial Intelligence ;$v11052 606 $aArtificial intelligence 606 $aData mining 606 $aOptical data processing 606 $aApplication software 606 $aComputers 606 $aData protection 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aData Mining and Knowledge Discovery$3https://scigraph.springernature.com/ontologies/product-market-codes/I18030 606 $aImage Processing and Computer Vision$3https://scigraph.springernature.com/ontologies/product-market-codes/I22021 606 $aComputer Appl. in Social and Behavioral Sciences$3https://scigraph.springernature.com/ontologies/product-market-codes/I23028 606 $aComputing Milieux$3https://scigraph.springernature.com/ontologies/product-market-codes/I24008 606 $aSecurity$3https://scigraph.springernature.com/ontologies/product-market-codes/I28000 615 0$aArtificial intelligence. 615 0$aData mining. 615 0$aOptical data processing. 615 0$aApplication software. 615 0$aComputers. 615 0$aData protection. 615 14$aArtificial Intelligence. 615 24$aData Mining and Knowledge Discovery. 615 24$aImage Processing and Computer Vision. 615 24$aComputer Appl. in Social and Behavioral Sciences. 615 24$aComputing Milieux. 615 24$aSecurity. 676 $a006.3 702 $aBerlingerio$b Michele$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aBonchi$b Francesco$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aGärtner$b Thomas$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aHurley$b Neil$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aIfrim$b Georgiana$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996466463803316 996 $aMachine Learning and Knowledge Discovery in Databases$9773712 997 $aUNISA