1. Natasa Sarafijanovic-Djukic and Jesse Davis - Fast Distance-based Anomaly Detection in Images Using an Inception-like Autoencoder
  2. Anton Björklund, Andreas Henelius, Emilia Oikarinen, Kimmo Kallonen and Kai Puolamäki - Sparse Robust Regression for Explaining Classifiers
  3. Vu-Linh Nguyen, Sébastien Destercke and Eyke Huellermeier - Epistemic Uncertainty Sampling
  4. Yannik Klein, Michael Rapp and Eneldo Loza Mencía - Efficient Discovery of Expressive Multi-label Rules using Relaxed Pruning
  5. Blaž Škrlj, Nada Lavrač and Jan Kralj - Symbolic Graph Embedding using Frequent Pattern Mining
  6. Matej Petković, Saso Dzeroski and Dragi Kocev - Ensemble-Based Feature Ranking for Semi-supervised Classification
  7. Bozhidar Stevanoski, Dragi Kocev, Aljaž Osojnik, Ivica Dimitrovski and Saso Dzeroski - Predicting thermal power consumption of the Mars Express satellite with data stream mining
  8. Colin Bellinger, Paula Branco and Luis Torgo - The CURE for Class Imbalance
  9. Domenico Mandaglio and Andrea Tagarelli - A Combinatorial Multi-Armed Bandit based method for Dynamic Consensus Community Detection in Temporal Networks
  10. Vitor Cerqueira, Luis Torgo and Carlos Soares -  Layered Learning for Early Anomaly Detection: Predicting Critical Health Episodes
  11. Kazumi Saito, Kouzou Ohara, Masahiro Kimura and Hiroshi Motoda - Resampling-based Framework for Unbiased Estimator of Node Centrality over Large Complex Network
  12. Pavlin Gregor Policar, Martin Strazar and Blaz Zupan - Embedding to Reference t-SNE Space Addresses Batch-Effects in Single-Cell Classification
  13. Dino Ienco and Ruggero G. Pensa - Deep Triplet-Driven Semi-Supervised Embedding Clustering
  14. Elena Battaglia and Ruggero G. Pensa - Parameter-less Tensor Co-clustering
  15. Michael Rapp, Eneldo Loza Mencía and Johannes Fürnkranz - On the Trade-off Between Consistency and Coverage in Multi-label Rule Learning Heuristics
  16. Amin Azari, Panagiotis Papapetrou, Stojan Denic and Gunnar Peters - Cellular Traffic Prediction and Classification: a comparative evaluation of LSTM and ARIMA
  17. Abhina Sharma, Jan N. van Rijn, Frank Hutter and Andreas Mueller - Hyperparameter Importance for Image Classification by Residual Networks
  18. Adriano Rivolli, Catarina Amaral, Luis Guardão, Cláudio Rebelo de Sá and Carlos Soares - KnowBots: Discovering Relevant Patterns in Chatbot Dialogues
  19. Angelo Impedovo, Michelangelo Ceci and Toon Calders - Efficient and Accurate Non-exhaustive Pattern-based Change Detection in Dynamic Networks
  20. Fabrizio Angiulli, Fabio Fassetti, Luigi Palopoli and Cristina Serrao - A density estimation approach for detecting and explaining exceptional values in categorical data
  21. Martin Atzmueller, Stefan Bloemheuvel and Benjamin Klöpper - A Framework for Human-Centered Exploration of Complex Event Log Graphs

Short Papers

  1. Sandy Moens, Boris Cule and Bart Goethals - A Sampling-based Approach for Discovering Subspace Clusters
  2. Vladimir Kuzmanovski, Mika Sulkava, Taru Palosuo and Jaakko Hollmen - Temporal analysis of adverse weather conditions affecting wheat production in Finland
  3. Andreia Conceição and João Gama - Main Factors Driving the Open Rate of Email Marketing Campaigns
  4. Ana Kostovska, Ilin Tolovski, Fatima Maikore, Larisa Soldatova and Pance Panov - Neurodegenerative Disease Data Ontology
  5. Vincent Branders, Guillaume Derval, Pierre Schaus and Pierre Dupont - Mining a maximum weighted set of disjoint submatrices
  6. Sofia Fernandes, Hadi Fanaee-T and Joao Gama - Evolving social networks analysis via tensor decompositions: from global event detection towards local pattern discovery and specification
  7. Nyoman Juniarta, Miguel Couceiro and Amedeo Napoli - A Unified Approach to Biclustering Based on Formal Concept Analysis and Interval Pattern Structure
  8. Hoang Son Pham, Siegfried Nijssen, Kim Mens, Dario Di Nucci, Tim Molderez, Coen De Roover, Johan Fabry and Vadim Zaytsev - Mining Patterns in Source Code using Tree Mining Algorithms
  9. Mohsen Ahmadi Fahandar and Eyke Hüllermeier - Feature Selection for Analogy-Based Learning to Rank
  10. Erik Dovgan, Bojan Leskošek, Gregor Jurak, Gregor Starc, Maroje Sorić and Mitja Luštrek - Enhancing BMI-Based Student Clustering by Considering Fitness as Key Attribute
  11. Samaneh Khoshrou and Mykola Pechenizkiy - Adaptive Long-term Ensemble Learning from Multiple High-dimensional Time-series
  12. Takayasu Fushimi, Kiyoto Iwasaki, Seiya Okubo and Kazumi Saito - Construction of Histogram with Variable Bin-width based on Change Point Detection
  13. Qianqian Gu and Ross King - On Recognizing Cats and Dogs in Chinese Paintings
  14. Aljaž Osojnik, Pance Panov and Saso Dzeroski - Utilizing Hierarchies in Tree-based Online Structured Output Prediction
  15. Julian Vexler and Stefan Kramer - Integrating LSTMs with Online Density Estimation for the Probabilistic Forecast of Energy Consumption
  16. André Correia, Carlos Soares and Alípio Jorge - Dataset Morphing to Analyze the Performance of Collaborative Filtering
  17. Kemilly Dearo Garcia, Elaine Ribeiro de Faria, Cláudio Rebelo de Sá, João Mendes-Moreira, Charu C. Aggarwal, André C.P.L.F de Carvalho and Joost N. Kok - Ensemble Clustering For Novelty Detection In Data Streams
  18. Cláudio Rebelo de Sá - Variance-based Feature Importance in Neural Networks
  19. Sascha Krstanovic and Heiko Paulheim - Fourier-based Parametrization of CNNs for Robust Time Series Forecasting

Important Dates

  • Paper submission (Extended): 25.6.2019
  • Author notification (Extended): 29.7.2019
  • PhD session abstract submission (Extended): 1.9.2019
  • PhD abstract notification (Extended): 4.9.2019
  • Camera ready (Extended): 20.8.2019
  • Author registration (For authors of accepted papers): 20.8.2019
  • Late Breaking Contributions: 8.9.2019
  • PhD Symposium registration (Extended): 8.9.2019
  • Early (non-author) registration (Extended): 16.9.2019
  • Regular registration: 27.10.2019
  • Conference: 28. - 30.10.2019

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