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ORCIDPKDD / ECML 2019: Würzburg, Germany
- Ulf Brefeld, Élisa Fromont
, Andreas Hotho, Arno J. Knobbe, Marloes H. Maathuis, Céline Robardet:
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2019, Würzburg, Germany, September 16-20, 2019, Proceedings, Part III. Lecture Notes in Computer Science 11908, Springer 2020, ISBN 978-3-030-46132-4
Reinforcement Learning and Bandits
- Alexander Zap, Tobias Joppen, Johannes Fürnkranz:
Deep Ordinal Reinforcement Learning. 3-18 - Denis Steckelmacher, Hélène Plisnier, Diederik M. Roijers, Ann Nowé:
Sample-Efficient Model-Free Reinforcement Learning with Off-Policy Critics. 19-34 - Quentin Debard, Jilles Steeve Dibangoye, Stéphane Canu, Christian Wolf:
Learning 3D Navigation Protocols on Touch Interfaces with Cooperative Multi-agent Reinforcement Learning. 35-52 - Kimia Nadjahi, Romain Laroche, Rémi Tachet des Combes:
Safe Policy Improvement with Soft Baseline Bootstrapping. 53-68 - Edouard Leurent, Odalric-Ambrym Maillard:
Practical Open-Loop Optimistic Planning. 69-85 - Mark Alexander Burgess, Archie C. Chapman, Paul Scott:
An Engineered Empirical Bernstein Bound. 86-102 - Wenling Shang, Douwe van der Wal, Herke van Hoof, Max Welling:
Stochastic Activation Actor Critic Methods. 103-117 - Zac Wellmer, James T. Kwok:
Policy Prediction Network: Model-Free Behavior Policy with Model-Based Learning in Continuous Action Space. 118-133 - Timo Bräm, Gino Brunner, Oliver Richter, Roger Wattenhofer:
Attentive Multi-task Deep Reinforcement Learning. 134-149 - Haoyu Zhao, Wei Chen:
Stochastic One-Sided Full-Information Bandit. 150-166 - Debabrota Basu, Pierre Senellart, Stéphane Bressan:
BelMan: An Information-Geometric Approach to Stochastic Bandits. 167-183
Ranking
- Rui Xia, Vincent Y. F. Tan, Louis Filstroff, Cédric Févotte:
A Ranking Model Motivated by Nonnegative Matrix Factorization with Applications to Tennis Tournaments. 187-203 - Klaus Brinker, Eyke Hüllermeier:
A Reduction of Label Ranking to Multiclass Classification. 204-219 - Cheng Li, Virgil Pavlu, Javed A. Aslam, Bingyu Wang, Kechen Qin:
Learning to Calibrate and Rerank Multi-label Predictions. 220-236 - Marius Köppel, Alexander Segner, Martin Wagener, Lukas Pensel, Andreas Karwath, Stefan Kramer:
Pairwise Learning to Rank by Neural Networks Revisited: Reconstruction, Theoretical Analysis and Practical Performance. 237-252 - Aleksandra Burashnikova, Yury Maximov, Massih-Reza Amini:
Sequential Learning over Implicit Feedback for Robust Large-Scale Recommender Systems. 253-269
Applied Data Science: Computer Vision and Explanation
- Omid Mohamad Nezami, Mark Dras, Len Hamey, Deborah Richards, Stephen Wan, Cécile Paris:
Automatic Recognition of Student Engagement Using Deep Learning and Facial Expression. 273-289 - Mark Thomas, Bruce Martin, Katie Kowarski, Briand J. Gaudet, Stan Matwin:
Marine Mammal Species Classification Using Convolutional Neural Networks and a Novel Acoustic Representation. 290-305 - Eduardo Hugo Sanchez, Mathieu Serrurier, Mathias Ortner:
Learning Disentangled Representations of Satellite Image Time Series. 306-321 - Kai Hou Yip, Nikolaos Nikolaou, Piero Coronica, Angelos Tsiaras, Billy Edwards, Quentin Changeat, Mario Morvan, Beth Biller, Sasha Hinkley, Jeffrey Salmond, Matthew Archer, Paul Sumption, Elodie Choquet, Remi Soummer, Laurent Pueyo, Ingo P. Waldmann:
Pushing the Limits of Exoplanet Discovery via Direct Imaging with Deep Learning. 322-338 - P. V. S. Avinesh, Yongli Ren, Christian M. Meyer, Jeffrey Chan, Zhifeng Bao, Mark Sanderson:
J3R: Joint Multi-task Learning of Ratings and Review Summaries for Explainable Recommendation. 339-355
Applied Data Science: Healthcare
- Nawshad Farruque, Osmar R. Zaïane, Randy Goebel:
Augmenting Semantic Representation of Depressive Language: From Forums to Microblogs. 359-375 - Konstantinos Nikolaidis, Stein Kristiansen, Vera Goebel, Thomas Plagemann, Knut Liestøl, Mohan S. Kankanhalli:
Augmenting Physiological Time Series Data: A Case Study for Sleep Apnea Detection. 376-399 - Jann Goschenhofer, Franz Michael Josef Pfister, Kamer Ali Yuksel, Bernd Bischl, Urban Fietzek, Janek Thomas:
Wearable-Based Parkinson's Disease Severity Monitoring Using Deep Learning. 400-415 - Christina Papagiannopoulou, René Parchen, Willem Waegeman:
Investigating Time Series Classification Techniques for Rapid Pathogen Identification with Single-Cell MALDI-TOF Mass Spectrum Data. 416-431 - Ali Mert Ertugrul, Yu-Ru Lin, Tugba Taskaya-Temizel:
CASTNet: Community-Attentive Spatio-Temporal Networks for Opioid Overdose Forecasting. 432-448
Applied Data Science: E-commerce, Finance, and Advertising
- Aritra Ghosh, Saayan Mitra, Somdeb Sarkhel, Jason Xie, Gang Wu, Viswanathan Swaminathan:
Scalable Bid Landscape Forecasting in Real-Time Bidding. 451-466 - Ahmed Rashed, Shayan Jawed, Jens Rehberg, Josif Grabocka, Lars Schmidt-Thieme, Andre Hintsches:
A Deep Multi-task Approach for Residual Value Forecasting. 467-482 - Hendra Suryanto, Charles Guan, Andrew Voumard, Ghassan Beydoun:
Transfer Learning in Credit Risk. 483-498 - Beibei Li, Beihong Jin, Taofeng Xue, Kunchi Liu, Qi Zhang, Sihua Tian:
Cold-Start Recommendation for On-Demand Cinemas. 499-515 - Nikita Kozodoi, Panagiotis Katsas, Stefan Lessmann, Luís Moreira-Matias, Konstantinos Papakonstantinou:
Shallow Self-learning for Reject Inference in Credit Scoring. 516-532
Applied Data Science: Rich Data
- Kevin Pasini, Mostepha Khouadjia, Allou Samé, Fabrice Ganansia, Latifa Oukhellou:
LSTM Encoder-Predictor for Short-Term Train Load Forecasting. 535-551 - Yiming Liao, Shuguang Wang, Eui-Hong Sam Han, Jongwuk Lee, Dongwon Lee:
Characterization and Early Detection of Evergreen News Articles. 552-568 - Tom Decroos, Jesse Davis:
Player Vectors: Characterizing Soccer Players' Playing Style from Match Event Streams. 569-584 - Hajer Salem, Moamar Sayed Mouchaweh:
A Semi-supervised and Online Learning Approach for Non-Intrusive Load Monitoring. 585-601 - Sushrut Bhalla, Matthew X. Yao, Jean-Pierre Hickey, Mark Crowley:
Compact Representation of a Multi-dimensional Combustion Manifold Using Deep Neural Networks. 602-617
Applied Data Science: Applications
- Shuai Zheng, Ahmed K. Farahat, Chetan Gupta:
Generative Adversarial Networks for Failure Prediction. 621-637 - Antoine Marot, Antoine Rosin, Laure Crochepierre, Benjamin Donnot, Pierre Pinson, Lydia Boudjeloud-Assala:
Interpreting Atypical Conditions in Systems with Deep Conditional Autoencoders: The Case of Electrical Consumption. 638-654 - Shuai Zheng, Chetan Gupta, Susumu Serita:
Manufacturing Dispatching Using Reinforcement and Transfer Learning. 655-671 - Guillaume Derval, Frédéric Docquier, Pierre Schaus:
An Aggregate Learning Approach for Interpretable Semi-supervised Population Prediction and Disaggregation Using Ancillary Data. 672-687 - Louay Abdelgawad, Peter Kluegl, Erdan Genc, Stefan Falkner, Frank Hutter:
Optimizing Neural Networks for Patent Classification. 688-703 - Lukas Pfahler, Jonathan Schill, Katharina Morik:
The Search for Equations - Learning to Identify Similarities Between Mathematical Expressions. 704-718 - Paulo Roberto de Oliveira da Costa, Jason Rhuggenaath, Yingqian Zhang, Alp Akcay, Wan-Jui Lee, Uzay Kaymak:
Data-Driven Policy on Feasibility Determination for the Train Shunting Problem. 719-734 - Lidia Contreras Ochando, Cèsar Ferri, José Hernández-Orallo, Fernando Martínez-Plumed, María José Ramírez-Quintana, Susumu Katayama:
Automated Data Transformation with Inductive Programming and Dynamic Background Knowledge. 735-751
Demo Track
- Lidia Contreras Ochando, César Ferri, José Hernández-Orallo, Fernando Martínez-Plumed, María José Ramírez-Quintana, Susumu Katayama:
BK-ADAPT: Dynamic Background Knowledge for Automating Data Transformation. 755-759 - Fabio Mercorio, Mario Mezzanzanica, Vincenzo Moscato, Antonio Picariello, Giancarlo Sperlì:
A Tool for Researchers: Querying Big Scholarly Data Through Graph Databases. 760-763 - Andreas Theissler, Stephan Frey, Jens Ehlert:
OCADaMi: One-Class Anomaly Detection and Data Mining Toolbox. 764-768 - Sören Laue, Matthias Mitterreiter, Joachim Giesen:
MatrixCalculus.org - Computing Derivatives of Matrix and Tensor Expressions. 769-772 - Nebula Alam, Khoi-Nguyen Tran, Sue Ann Chen, John Wagner, Josh Andres, Mukesh K. Mohania:
Towards a Predictive Patent Analytics and Evaluation Platform. 773-776 - Talmaj Marinc, Serhan Gül, Cornelius Hellge, Peter Schüßler, Thomas Riegel, Peter Amon:
A Virtualized Video Surveillance System for Public Transportation. 777-780 - Oleksandra Levchenko, Boyan Kolev, Djamel Edine Yagoubi, Dennis E. Shasha, Themis Palpanas, Patrick Valduriez, Reza Akbarinia, Florent Masseglia:
Distributed Algorithms to Find Similar Time Series. 781-785 - José Carlos Coutinho, João Mendes-Moreira, Cláudio Rebelo de Sá:
UnFOOT: Unsupervised Football Analytics Tool. 786-789 - Jingwei Zuo, Karine Zeitouni, Yehia Taher:
ISETS: Incremental Shapelet Extraction from Time Series Stream. 790-793 - Reuben Borrison, Benjamin Klöpper, Sunil Saini:
Industrial Event Log Analyzer - Self-service Data Mining for Domain Experts. 794-798
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