ECML-PKDD 2018

94 papers

A Blended Metric for Multi-Label Optimisation and Evaluation Laurence A. F. Park, Jesse Read
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A Discriminative Model for Identifying Readers and Assessing Text Comprehension from Eye Movements Silvia Makowski, Lena A. Jäger, Ahmed AbdelWahab, Niels Landwehr, Tobias Scheffer
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A Left-to-Right Algorithm for Likelihood Estimation in Gamma-Poisson Factor Analysis Joan Capdevila, Jesús Cerquides, Jordi Torres, François Petitjean, Wray L. Buntine
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A Unified Framework for Domain Adaptation Using Metric Learning on Manifolds Sridhar Mahadevan, Bamdev Mishra, Shalini Ghosh
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An Efficient Algorithm for Computing Entropic Measures of Feature Subsets Frédéric Pennerath
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Anytime Subgroup Discovery in Numerical Domains with Guarantees Aimene Belfodil, Adnene Belfodil, Mehdi Kaytoue
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Auxiliary Guided Autoregressive Variational Autoencoders Thomas Lucas, Jakob Verbeek
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AWX: An Integrated Approach to Hierarchical-Multilabel Classification Luca Masera, Enrico Blanzieri
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Axiomatic Characterization of AdaBoost and the Multiplicative Weight Update Procedure Ibrahim M. Alabdulmohsin
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Beyond Outlier Detection: LookOut for Pictorial Explanation Nikhil Gupta, Dhivya Eswaran, Neil Shah, Leman Akoglu, Christos Faloutsos
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Block CUR: Decomposing Matrices Using Groups of Columns Urvashi Oswal, Swayambhoo Jain, Kevin S. Xu, Brian Eriksson
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Causal Inference on Multivariate and Mixed-Type Data Alexander Marx, Jilles Vreeken
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Clustering in the Presence of Concept Drift Richard Hugh Moulton, Herna L. Viktor, Nathalie Japkowicz, João Gama
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ConOut: Contextual Outlier Detection with Multiple Contexts: Application to Ad Fraud Meghanath Macha Yadagiri, Deepak Pai, Leman Akoglu
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Constructive Aggregation and Its Application to Forecasting with Dynamic Ensembles Vítor Cerqueira, Fábio Pinto, Luís Torgo, Carlos Soares, Nuno Moniz
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Controlling and Visualizing the Precision-Recall Tradeoff for External Performance Indices Blaise Hanczar, Mohamed Nadif
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Cooperative Multi-Agent Policy Gradient Guillaume Bono, Jilles Steeve Dibangoye, Laëtitia Matignon, Florian Pereyron, Olivier Simonin
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Deep F-Measure Maximization in Multi-Label Classification: A Comparative Study Stijn Decubber, Thomas Mortier, Krzysztof Dembczynski, Willem Waegeman
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Deep Learning Architecture Search by Neuro-Cell-Based Evolution with Function-Preserving Mutations Martin Wistuba
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Detecting Autism by Analyzing a Simulated Social Interaction Hanna Drimalla, Niels Landwehr, Irina Baskow, Behnoush Behnia, Stefan Roepke, Isabel Dziobek, Tobias Scheffer
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Differentially Private Hypothesis Transfer Learning Yang Wang, Quanquan Gu, Donald E. Brown
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Discovering Spatio-Temporal Latent Influence in Geographical Attention Dynamics Minoru Higuchi, Kanji Matsutani, Masahito Kumano, Masahiro Kimura
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Discovering Urban Travel Demands Through Dynamic Zone Correlation in Location-Based Social Networks Wangsu Hu, Zijun Yao, Sen Yang, Shuhong Chen, Peter Jing Jin
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Domain Adaption in One-Shot Learning Nanqing Dong, Eric P. Xing
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Dynamic Hierarchies in Temporal Directed Networks Nikolaj Tatti
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Efficient Decentralized Deep Learning by Dynamic Model Averaging Michael Kamp, Linara Adilova, Joachim Sicking, Fabian Hüger, Peter Schlicht, Tim Wirtz, Stefan Wrobel
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Efficient Estimation of AUC in a Sliding Window Nikolaj Tatti
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Evaluation Procedures for Forecasting with Spatio-Temporal Data Mariana Oliveira, Luís Torgo, Vítor Santos Costa
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Exploration Enhanced Expected Improvement for Bayesian Optimization Julian Berk, Vu Nguyen, Sunil Gupta, Santu Rana, Svetha Venkatesh
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Face-Cap: Image Captioning Using Facial Expression Analysis Omid Mohamad Nezami, Mark Dras, Peter Anderson, Len Hamey
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Fast and Provably Effective Multi-View Classification with Landmark-Based SVM Valentina Zantedeschi, Rémi Emonet, Marc Sebban
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Feature Selection for Unsupervised Domain Adaptation Using Optimal Transport Léo Gautheron, Ievgen Redko, Carole Lartizien
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Frame-Based Optimal Design Sebastian Mair, Yannick Rudolph, Vanessa Closius, Ulf Brefeld
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GeoDCF: Deep Collaborative Filtering with Multifaceted Contextual Information in Location-Based Social Networks Dimitrios Rafailidis, Fabio Crestani
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GridWatch: Sensor Placement and Anomaly Detection in the Electrical Grid Bryan Hooi, Dhivya Eswaran, Hyun Ah Song, Amritanshu Pandey, Marko Jereminov, Larry T. Pileggi, Christos Faloutsos
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Group Anomaly Detection Using Deep Generative Models Raghavendra Chalapathy, Edward Toth, Sanjay Chawla
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Hierarchical Active Learning with Proportion Feedback on Regions Zhipeng Luo, Milos Hauskrecht
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How Your Supporters and Opponents Define Your Interestingness Bruno Crémilleux, Arnaud Giacometti, Arnaud Soulet
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Hyperparameter Learning for Conditional Kernel Mean Embeddings with Rademacher Complexity Bounds Kelvin Hsu, Richard Nock, Fabio Ramos
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Identifying and Alleviating Concept Drift in Streaming Tensor Decomposition Ravdeep Pasricha, Ekta Gujral, Evangelos E. Papalexakis
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Image Anomaly Detection with Generative Adversarial Networks Lucas Deecke, Robert A. Vandermeulen, Lukas Ruff, Stephan Mandt, Marius Kloft
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Image-to-Markup Generation via Paired Adversarial Learning Jin-Wen Wu, Fei Yin, Yan-Ming Zhang, Xu-Yao Zhang, Cheng-Lin Liu
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Incorporating Privileged Information to Unsupervised Anomaly Detection Shubhranshu Shekhar, Leman Akoglu
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Inferring Continuous Latent Preference on Transition Intervals for Next Point-of-Interest Recommendation Jing He, Xin Li, Lejian Liao, Mingzhong Wang
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Information-Theoretic Transfer Learning Framework for Bayesian Optimisation Anil Ramachandran, Sunil Gupta, Santu Rana, Svetha Venkatesh
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Joint Autoencoders: A Flexible Meta-Learning Framework Baruch Epstein, Ron Meir, Tomer Michaeli
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L1-Depth Revisited: A Robust Angle-Based Outlier Factor in High-Dimensional Space Ninh Pham
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Lambert Matrix Factorization Arto Klami, Jarkko Lagus, Joseph Sakaya
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Large-Scale Nonlinear Variable Selection via Kernel Random Features Magda Gregorová, Jason Ramapuram, Alexandros Kalousis, Stéphane Marchand-Maillet
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Learning Multi-Granularity Dynamic Network Representations for Social Recommendation Peng Liu, Lemei Zhang, Jon Atle Gulla
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Local Topological Data Analysis to Uncover the Global Structure of Data Approaching Graph-Structured Topologies Robin Vandaele, Tijl De Bie, Yvan Saeys
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MASAGA: A Linearly-Convergent Stochastic First-Order Method for Optimization on Manifolds Reza Babanezhad, Issam H. Laradji, Alireza Shafaei, Mark Schmidt
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MaxGain: Regularisation of Neural Networks by Constraining Activation Magnitudes Henry Gouk, Bernhard Pfahringer, Eibe Frank, Michael J. Cree
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MetaBags: Bagged Meta-Decision Trees for Regression Jihed Khiari, Luís Moreira-Matias, Ammar Shaker, Bernard Zenko, Saso Dzeroski
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Mining Periodic Patterns with a MDL Criterion Esther Galbrun, Peggy Cellier, Nikolaj Tatti, Alexandre Termier, Bruno Crémilleux
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Mining Tree Patterns with Partially Injective Homomorphisms Till Hendrik Schulz, Tamás Horváth, Pascal Welke, Stefan Wrobel
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Modular Dimensionality Reduction Henry W. J. Reeve, Tingting Mu, Gavin Brown
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Multiple Instance Learning with Bag-Level Randomized Trees Tomás Komárek, Petr Somol
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Nyström-SGD: Fast Learning of Kernel-Classifiers with Conditioned Stochastic Gradient Descent Lukas Pfahler, Katharina Morik
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On Finer Control of Information Flow in LSTMs Hang Gao, Tim Oates
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One-Class Quantification Denis Moreira dos Reis, André Gustavo Maletzke, Everton Alvares Cherman, Gustavo Enrique De Almeida Prado Alves Batista
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ONE-M: Modeling the Co-Evolution of Opinions and Network Connections Aastha Nigam, Kijung Shin, Ashwin Bahulkar, Bryan Hooi, David Hachen, Boleslaw K. Szymanski, Christos Faloutsos, Nitesh V. Chawla
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Online Feature Selection by Adaptive Sub-Gradient Methods Tingting Zhai, Hao Wang, Frédéric Koriche, Yang Gao
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Online Learning of Weighted Relational Rules for Complex Event Recognition Nikos Katzouris, Evangelos Michelioudakis, Alexander Artikis, Georgios Paliouras
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Ontology Alignment Based on Word Embedding and Random Forest Classification Ikechukwu Nkisi-Orji, Nirmalie Wiratunga, Stewart Massie, Kit-Ying Hui, Rachel Heaven
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Ordinal Label Proportions Rafael Poyiadzi, Raúl Santos-Rodríguez, Tijl De Bie
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Parametric T-Distributed Stochastic Exemplar-Centered Embedding Martin Renqiang Min, Hongyu Guo, Dinghan Shen
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Pedestrian Trajectory Prediction with Structured Memory Hierarchies Tharindu Fernando, Simon Denman, Sridha Sridharan, Clinton Fookes
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Personalized Thread Recommendation for MOOC Discussion Forums Andrew S. Lan, Jonathan C. Spencer, Ziqi Chen, Christopher G. Brinton, Mung Chiang
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POLAR: Attention-Based CNN for One-Shot Personalized Article Recommendation Zhengxiao Du, Jie Tang, Yuhui Ding
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Privacy Preserving Synthetic Data Release Using Deep Learning Nazmiye Ceren Abay, Yan Zhou, Murat Kantarcioglu, Bhavani Thuraisingham, Latanya Sweeney
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Revisiting Conditional Functional Dependency Discovery: Splitting the "c" from the "FD" Joeri Rammelaere, Floris Geerts
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Risk-Averse Matchings over Uncertain Graph Databases Charalampos E. Tsourakakis, Shreyas Sekar, Johnson Lam, Liu Yang
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Robust Super-Level Set Estimation Using Gaussian Processes Andrea Zanette, Junzi Zhang, Mykel J. Kochenderfer
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Scalable and Interpretable One-Class SVMs with Deep Learning and Random Fourier Features Minh-Nghia Nguyen, Ngo Anh Vien
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Scalable Nonlinear AUC Maximization Methods Majdi Khalid, Indrakshi Ray, Hamidreza Chitsaz
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Semi-Supervised Blockmodelling with Pairwise Guidance Mohadeseh Ganji, Jeffrey Chan, Peter J. Stuckey, James Bailey, Christopher Leckie, Kotagiri Ramamohanarao, Laurence A. F. Park
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ShapeShifter: Robust Physical Adversarial Attack on Faster R-CNN Object Detector Shang-Tse Chen, Cory Cornelius, Jason Martin, Duen Horng (Polo) Chau
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Similarity Modeling on Heterogeneous Networks via Automatic Path Discovery Carl Yang, Mengxiong Liu, Frank He, Xikun Zhang, Jian Peng, Jiawei Han
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Social-Affiliation Networks: Patterns and the SOAR Model Dhivya Eswaran, Reihaneh Rabbany, Artur W. Dubrawski, Christos Faloutsos
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SpectralLeader: Online Spectral Learning for Single Topic Models Tong Yu, Branislav Kveton, Zheng Wen, Hung Bui, Ole J. Mengshoel
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Sqn2Vec: Learning Sequence Representation via Sequential Patterns with a Gap Constraint Dang Nguyen, Wei Luo, Tu Dinh Nguyen, Svetha Venkatesh, Dinh Q. Phung
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Temporally Evolving Community Detection and Prediction in Content-Centric Networks Ana Paula Appel, Renato Luiz de Freitas Cunha, Charu C. Aggarwal, Marcela Megumi Terakado
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Think Before You Discard: Accurate Triangle Counting in Graph Streams with Deletions Kijung Shin, Jisu Kim, Bryan Hooi, Christos Faloutsos
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Time Warp Invariant Dictionary Learning for Time Series Clustering: Application to Music Data Stream Analysis Saeed Varasteh Yazdi, Ahlame Douzal Chouakria, Patrick Gallinari, Manuel Moussallam
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Toward an Understanding of Adversarial Examples in Clinical Trials Konstantinos Papangelou, Konstantinos Sechidis, James Weatherall, Gavin Brown
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Toward Interpretable Deep Reinforcement Learning with Linear Model U-Trees Guiliang Liu, Oliver Schulte, Wang Zhu, Qingcan Li
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Towards Efficient Forward Propagation on Resource-Constrained Systems Günther Schindler, Matthias Zöhrer, Franz Pernkopf, Holger Fröning
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Towards More Reliable Transfer Learning Zirui Wang, Jaime G. Carbonell
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Using Supervised Pretraining to Improve Generalization of Neural Networks on Binary Classification Problems Alex Yuxuan Peng, Yun Sing Koh, Patricia Riddle, Bernhard Pfahringer
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Variational Bayes for Mixture Models with Censored Data Masahiro Kohjima, Tatsushi Matsubayashi, Hiroyuki Toda
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VC-Dimension Based Generalization Bounds for Relational Learning Ondrej Kuzelka, Yuyi Wang, Steven Schockaert
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Visualizing the Feature Importance for Black Box Models Giuseppe Casalicchio, Christoph Molnar, Bernd Bischl
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Web-Induced Heterogeneous Transfer Learning with Sample Selection Sanatan Sukhija, Narayanan Chatapuram Krishnan
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