Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2018, Dublin, Ireland, September 10–14, 2018, Proceedings, Part II

Front Matter ....Pages I-XXX
Front Matter ....Pages 1-1
 Temporally Evolving Community Detection and Prediction in Content-Centric Networks  (Ana Paula Appel, Renato L. F. Cunha, Charu C. Aggarwal, Marcela Megumi Terakado)....Pages 3-18
 Local Topological Data Analysis to Uncover the Global Structure of Data Approaching Graph-Structured Topologies  (Robin Vandaele, Tijl De Bie, Yvan Saeys)....Pages 19-36
 Similarity Modeling on Heterogeneous Networks via Automatic Path Discovery  (Carl Yang, Mengxiong Liu, Frank He, Xikun Zhang, Jian Peng, Jiawei Han)....Pages 37-54
 Dynamic Hierarchies in Temporal Directed Networks  (Nikolaj Tatti)....Pages 55-70
 Risk-Averse Matchings over Uncertain Graph Databases  (Charalampos E. Tsourakakis, Shreyas Sekar, Johnson Lam, Liu Yang)....Pages 71-87
 Discovering Urban Travel Demands Through Dynamic Zone Correlation in Location-Based Social Networks  (Wangsu Hu, Zijun Yao, Sen Yang, Shuhong Chen, Peter J. Jin)....Pages 88-104
 Social-Affiliation Networks: Patterns and the SOAR Model  (Dhivya Eswaran, Reihaneh Rabbany, Artur W. Dubrawski, Christos Faloutsos)....Pages 105-121
 ONE-M: Modeling the Co-evolution of Opinions and Network Connections  (Aastha Nigam, Kijung Shin, Ashwin Bahulkar, Bryan Hooi, David Hachen, Boleslaw K. Szymanski et al.)....Pages 122-140
 Think Before You Discard: Accurate Triangle Counting in Graph Streams with Deletions  (Kijung Shin, Jisu Kim, Bryan Hooi, Christos Faloutsos)....Pages 141-157
 Semi-supervised Blockmodelling with Pairwise Guidance  (Mohadeseh Ganji, Jeffrey Chan, Peter J. Stuckey, James Bailey, Christopher Leckie, Kotagiri Ramamohanarao et al.)....Pages 158-174
Front Matter ....Pages 175-175
 Large-Scale Nonlinear Variable Selection via Kernel Random Features  (Magda Gregorová, Jason Ramapuram, Alexandros Kalousis, Stéphane Marchand-Maillet)....Pages 177-192
 Fast and Provably Effective Multi-view Classification with Landmark-Based SVM  (Valentina Zantedeschi, Rémi Emonet, Marc Sebban)....Pages 193-208
 Nyström-SGD: Fast Learning of Kernel-Classifiers with Conditioned Stochastic Gradient Descent  (Lukas Pfahler, Katharina Morik)....Pages 209-224
Front Matter ....Pages 225-225
 Hyperparameter Learning for Conditional Kernel Mean Embeddings with Rademacher Complexity Bounds  (Kelvin Hsu, Richard Nock, Fabio Ramos)....Pages 227-242
 Deep Learning Architecture Search by Neuro-Cell-Based Evolution with Function-Preserving Mutations  (Martin Wistuba)....Pages 243-258
 VC-Dimension Based Generalization Bounds for Relational Learning  (Ondřej Kuželka, Yuyi Wang, Steven Schockaert)....Pages 259-275
 Robust Super-Level Set Estimation Using Gaussian Processes  (Andrea Zanette, Junzi Zhang, Mykel J. Kochenderfer)....Pages 276-291
 Scalable Nonlinear AUC Maximization Methods  (Majdi Khalid, Indrakshi Ray, Hamidreza Chitsaz)....Pages 292-307
Front Matter ....Pages 309-309
 Lambert Matrix Factorization  (Arto Klami, Jarkko Lagus, Joseph Sakaya)....Pages 311-326
 Identifying and Alleviating Concept Drift in Streaming Tensor Decomposition  (Ravdeep Pasricha, Ekta Gujral, Evangelos E. Papalexakis)....Pages 327-343
 MASAGA: A Linearly-Convergent Stochastic First-Order Method for Optimization on Manifolds  (Reza Babanezhad, Issam H. Laradji, Alireza Shafaei, Mark Schmidt)....Pages 344-359
 Block CUR: Decomposing Matrices Using Groups of Columns  (Urvashi Oswal, Swayambhoo Jain, Kevin S. Xu, Brian Eriksson)....Pages 360-376
Front Matter ....Pages 377-377
 \(\mathtt{SpectralLeader}\): Online Spectral Learning for Single Topic Models  (Tong Yu, Branislav Kveton, Zheng Wen, Hung Bui, Ole J. Mengshoel)....Pages 379-395
 Online Learning of Weighted Relational Rules for Complex Event Recognition  (Nikos Katzouris, Evangelos Michelioudakis, Alexander Artikis, Georgios Paliouras)....Pages 396-413
 Toward Interpretable Deep Reinforcement Learning with Linear Model U-Trees  (Guiliang Liu, Oliver Schulte, Wang Zhu, Qingcan Li)....Pages 414-429
 Online Feature Selection by Adaptive Sub-gradient Methods  (Tingting Zhai, Hao Wang, Frédéric Koriche, Yang Gao)....Pages 430-446
 Frame-Based Optimal Design  (Sebastian Mair, Yannick Rudolph, Vanessa Closius, Ulf Brefeld)....Pages 447-463
 Hierarchical Active Learning with Proportion Feedback on Regions  (Zhipeng Luo, Milos Hauskrecht)....Pages 464-480
Front Matter ....Pages 481-481
 An Efficient Algorithm for Computing Entropic Measures of Feature Subsets  (Frédéric Pennerath)....Pages 483-499
 Anytime Subgroup Discovery in Numerical Domains with Guarantees  (Aimene Belfodil, Adnene Belfodil, Mehdi Kaytoue)....Pages 500-516
 Discovering Spatio-Temporal Latent Influence in Geographical Attention Dynamics  (Minoru Higuchi, Kanji Matsutani, Masahito Kumano, Masahiro Kimura)....Pages 517-534
 Mining Periodic Patterns with a MDL Criterion  (Esther Galbrun, Peggy Cellier, Nikolaj Tatti, Alexandre Termier, Bruno Crémilleux)....Pages 535-551
 Revisiting Conditional Functional Dependency Discovery: Splitting the “C” from the “FD”  (Joeri Rammelaere, Floris Geerts)....Pages 552-568
 Sqn2Vec: Learning Sequence Representation via Sequential Patterns with a Gap Constraint  (Dang Nguyen, Wei Luo, Tu Dinh Nguyen, Svetha Venkatesh, Dinh Phung)....Pages 569-584
 Mining Tree Patterns with Partially Injective Homomorphisms  (Till Hendrik Schulz, Tamás Horváth, Pascal Welke, Stefan Wrobel)....Pages 585-601
Front Matter ....Pages 603-603
 Variational Bayes for Mixture Models with Censored Data  (Masahiro Kohjima, Tatsushi Matsubayashi, Hiroyuki Toda)....Pages 605-620
 Exploration Enhanced Expected Improvement for Bayesian Optimization  (Julian Berk, Vu Nguyen, Sunil Gupta, Santu Rana, Svetha Venkatesh)....Pages 621-637
 A Left-to-Right Algorithm for Likelihood Estimation in Gamma-Poisson Factor Analysis  (Joan Capdevila, Jesús Cerquides, Jordi Torres, François Petitjean, Wray Buntine)....Pages 638-654
 Causal Inference on Multivariate and Mixed-Type Data  (Alexander Marx, Jilles Vreeken)....Pages 655-671
Front Matter ....Pages 673-673
 POLAR: Attention-Based CNN for One-Shot Personalized Article Recommendation  (Zhengxiao Du, Jie Tang, Yuhui Ding)....Pages 675-690
 Learning Multi-granularity Dynamic Network Representations for Social Recommendation  (Peng Liu, Lemei Zhang, Jon Atle Gulla)....Pages 691-708
 GeoDCF: Deep Collaborative Filtering with Multifaceted Contextual Information in Location-Based Social Networks  (Dimitrios Rafailidis, Fabio Crestani)....Pages 709-724
 Personalized Thread Recommendation for MOOC Discussion Forums  (Andrew S. Lan, Jonathan C. Spencer, Ziqi Chen, Christopher G. Brinton, Mung Chiang)....Pages 725-740
 Inferring Continuous Latent Preference on Transition Intervals for Next Point-of-Interest Recommendation  (Jing He, Xin Li, Lejian Liao, Mingzhong Wang)....Pages 741-756
Front Matter ....Pages 757-757
 Feature Selection for Unsupervised Domain Adaptation Using Optimal Transport  (Leo Gautheron, Ievgen Redko, Carole Lartizien)....Pages 759-776
 Web-Induced Heterogeneous Transfer Learning with Sample Selection  (Sanatan Sukhija, Narayanan C. Krishnan)....Pages 777-793
 Towards More Reliable Transfer Learning  (Zirui Wang, Jaime Carbonell)....Pages 794-810
 Differentially Private Hypothesis Transfer Learning  (Yang Wang, Quanquan Gu, Donald Brown)....Pages 811-826
 Information-Theoretic Transfer Learning Framework for Bayesian Optimisation  (Anil Ramachandran, Sunil Gupta, Santu Rana, Svetha Venkatesh)....Pages 827-842
 A Unified Framework for Domain Adaptation Using Metric Learning on Manifolds  (Sridhar Mahadevan, Bamdev Mishra, Shalini Ghosh)....Pages 843-860
Back Matter ....Pages 861-866