LEADER 07409nam 22007695 450 001 996466463503316 005 20200703200919.0 010 $a3-030-10925-9 024 7 $a10.1007/978-3-030-10925-7 035 $a(CKB)4100000007522526 035 $a(DE-He213)978-3-030-10925-7 035 $a(MiAaPQ)EBC5921403 035 $a(PPN)233799516 035 $a(EXLCZ)994100000007522526 100 $a20190117d2019 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] $eEuropean Conference, ECML PKDD 2018, Dublin, Ireland, September 10?14, 2018, Proceedings, Part I /$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 (XXXVIII, 740 p. 451 illus., 159 illus. in color.) 225 1 $aLecture Notes in Artificial Intelligence ;$v11051 300 $aIncludes index. 311 $a3-030-10924-0 327 $aAdversarial Learning -- Image Anomaly Detection with Generative Adversarial Networks -- Image-to-Markup Generation via Paired Adversarial Learning -- Toward an Understanding of Adversarial Examples in Clinical Trials -- ShapeShifter: Robust Physical Adversarial Attack on Faster R-CNN Object Detector -- Anomaly and Outlier Detection -- GridWatch: Sensor Placement and Anomaly Detection in the Electrical Grid -- Incorporating Privileged Information to Unsupervised Anomaly Detection -- L1-Depth Revisited: A Robust Angle-based Outlier Factor in High-dimensional Space -- Beyond Outlier Detection: LookOut for Pictorial Explanation -- Scalable and Interpretable One-class SVMs with Deep Learning and Random Fourier Features -- Group Anomaly Detection using Deep Generative Models -- Applications -- A Discriminative Model for Identifying Readers and Assessing Text Comprehension from Eye Movements -- Face-Cap: Image Captioning using Facial Expression Analysis -- Pedestrian Trajectory Prediction with Structured Memory Hierarchies -- Classification -- Multiple Instance Learning with Bag-level Randomized Trees -- One-class Quantification -- Deep F-Measure Maximization in Multi-Label Classification: A Comparative Study -- Ordinal Label Proportions -- AWX: An Integrated Approach to Hierarchical-Multilabel Classification -- Clustering and Unsupervised Learning -- Clustering in the Presence of Concept Drift -- Time Warp Invariant Dictionary Learning for Time Series Clustering -- How Your Supporters and Opponents Define Your Interestingness -- Deep Learning -- Efficient Decentralized Deep Learning by Dynamic Model Averaging -- Using Supervised Pretraining to Improve Generalization of Neural Networks on Binary Classification Problems -- Towards Efficient Forward Propagation on Resource-Constrained Systems -- Auxiliary Guided Autoregressive Variational Autoencoders -- Cooperative Multi-Agent Policy Gradient -- Parametric t-Distributed Stochastic Exemplar-centered Embedding -- Joint autoencoders: a flexible meta-learning framework -- Privacy Preserving Synthetic Data Release Using Deep Learning -- On Finer Control of Information Flow in LSTMs -- MaxGain: Regularisation of Neural Networks by Constraining Activation Magnitudes -- Ontology alignment based on word embedding and random forest classification -- Domain Adaption in One-Shot Learning -- Ensemble Methods -- Axiomatic Characterization of AdaBoost and the Multiplicative Weight Update Procedure -- Modular Dimensionality Reduction -- Constructive Aggregation and its Application to Forecasting with Dynamic Ensembles -- MetaBags: Bagged Meta-Decision Trees for Regression -- Evaluation -- Visualizing the Feature Importance for Black Box Models -- Efficient estimation of AUC in a sliding window -- Controlling and visualizing the precision-recall tradeoff for external performance indices -- Evaluation Procedures for Forecasting with Spatio-Temporal Data -- A Blended Metric for Multi-label Optimisation and Evaluation. 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 ;$v11051 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 $a006.31 702 $aBerlingerio$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 $a996466463503316 996 $aMachine Learning and Knowledge Discovery in Databases$9773712 997 $aUNISA