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082 0 4 _a006.312
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245 1 0 _aMachine Learning and Knowledge Discovery in Databases
_h[electronic resource] :
_bEuropean Conference, ECML PKDD 2017, Skopje, Macedonia, September 18-22, 2017, Proceedings, Part I /
_cedited by Michelangelo Ceci, Jaakko Hollmén, Ljupčo Todorovski, Celine Vens, Sašo Džeroski.
250 _a1st ed. 2017.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2017.
300 _aLXIII, 852 p. 245 illus.
_bonline resource.
336 _atext
_btxt
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337 _acomputer
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338 _aonline resource
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490 1 _aLecture Notes in Artificial Intelligence,
_x2945-9141 ;
_v10534
505 0 _aAnomaly Detection -- Concentration Free Outlier Detection -- Efficient top rank optimization with gradient boosting for supervised anomaly detection -- Robust, Deep and Inductive Anomaly Detection -- Sentiment Informed Cyberbullying Detection in Social Media -- zooRank: Ranking Suspicious Activities in Time-Evolving Tensors -- Computer Vision -- Alternative Semantic Representations for Zero-Shot Human Action Recognition -- Early Active Learning with Pairwise Constraint for Person Re-identification -- Guiding InfoGAN with Semi-Supervision -- Scatteract: Automated extraction of data from scatter plots -- Unsupervised Diverse Colorization via Generative Adversarial Networks -- Ensembles and Meta Learning -- Dynamic Ensemble Selection with Probabilistic Classifier Chains -- Ensemble-Compression: A New Method for Parallel Training of Deep Neural Networks -- Fast and Accurate Density Estimation with Extremely Randomized Cutset Networks -- Feature Selection and Extraction -- Deep Discrete Hashing with Self-supervised Labels -- Including multi-feature interactions and redundancy for feature ranking in mixed datasets -- Non-redundant Spectral Dimensionality Reduction -- Rethinking Unsupervised Feature Selection: From Pseudo Labels to Pseudo Must-links -- SetExpan: Corpus-based Set Expansion via Context Feature Selection and Rank Ensemble -- Kernel Methods -- Bayesian Nonlinear Support Vector Machines for Big Data -- Entropic Trace Estimation for Log Determinants -- Fair Kernel Learning -- GaKCo: a Fast Gapped k-mer string Kernel using Counting -- Graph Enhanced Memory Networks for Sentiment Analysis -- Kernel Sequential Monte Carlo -- Learning Lukasiewicz Logic Fragments by Quadratic Programming -- Nystrom sketching -- Learning and Optimization -- Crossprop: learning representations by stochastic meta-gradient descent in neural networks -- Distributed Stochastic Optimization of the Regularized Risk via Saddle-point Problem -- Speeding up Hyper-parameter Optimization by Extrapolation of Learning Curves using Previous Builds -- Matrix and Tensor Factorization -- Comparative Study of Inference Methods for Bayesian Nonnegative Matrix Factorisation -- Content-Based Social Recommendation with Poisson Matrix Factorization -- C-SALT: Mining Class-Speci_c ALTerations in Boolean Matrix Factorization -- Feature Extraction for Incomplete Data via Low-rank Tucker Decomposition -- Structurally Regularized Non-negative Tensor Factorization for Spatio-temporal Pattern Discoveries -- Networks and Graphs -- Attributed Graph Clustering with Unimodal Normalized Cut -- K-clique-graphs for Dense Subgraph Discovery -- Learning and Scaling Directed Networks via Graph Embedding -- Local Lanczos Spectral Approximation for Membership Identification -- Regularizing Knowledge Graph Embeddings via Equivalence and Inversion Axioms -- Survival Factorization for Topical Cascades on Diffusion Networks -- The network-untangling problem: From interactions to activity timelines.-TransT: Type-based Multiple Embedding Representations forKnowledge Graph Completion -- Neural Networks and Deep Learning -- A network Architecture for Multi-multi Instance Learning -- CON-S2V: A Generic Framework for Incorporating Extra-Sentential Context into Sen2Vec -- Deep Over-sampling Framework for Classifying Imbalanced Data -- FCNNs: Fourier Convolutional Neural Networks -- Joint User Modeling across Aligned Heterogeneous Sites using Neural Networks -- Sequence Generation with Target Attention -- Wikipedia Vandal Early Detection: from User Behavior to User Embedding. .
520 _aThe three volume proceedings LNAI 10534 - 10536 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2017, held in Skopje, Macedonia, in September 2017. The total of 101 regular papers presented in part I and part II was carefully reviewed and selected from 364 submissions; there are 47 papers in the applied data science, nectar and demo track. The contributions were organized in topical sections named as follows: Part I: anomaly detection; computer vision; ensembles and meta learning; feature selection and extraction; kernel methods; learning and optimization, matrix and tensor factorization; networks and graphs; neural networks and deep learning. Part II: pattern and sequence mining; privacy and security; probabilistic models and methods; recommendation; regression; reinforcement learning; subgroup discovery; time series and streams; transfer and multi-task learning; unsupervised and semisupervised learning. Part III: applied data science track; nectar track; and demo track.
650 0 _aData mining.
_93907
650 0 _aArtificial intelligence.
_93407
650 0 _aComputer vision.
_9170062
650 0 _aApplication software.
_9170063
650 0 _aData protection.
_97245
650 0 _aComputers.
_98172
650 1 4 _aData Mining and Knowledge Discovery.
_9170064
650 2 4 _aArtificial Intelligence.
_93407
650 2 4 _aComputer Vision.
_9170065
650 2 4 _aComputer and Information Systems Applications.
_9170066
650 2 4 _aData and Information Security.
_931990
650 2 4 _aComputing Milieux.
_955441
700 1 _aCeci, Michelangelo.
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700 1 _aHollmén, Jaakko.
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700 1 _aTodorovski, Ljupčo.
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700 1 _aVens, Celine.
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700 1 _aDžeroski, Sašo.
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776 0 8 _iPrinted edition:
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776 0 8 _iPrinted edition:
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830 0 _aLecture Notes in Artificial Intelligence,
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