Sebastian Kauschke
First name(s): Sebastian
Last name(s): Kauschke

Publications of Sebastian Kauschke
2019
Sebastian Kauschke, David Hermann Lehmann and Johannes Fürnkranz, [TO APPEAR] Patching Deep Neural Networks for Nonstationary Environments, in: Proceedings of the 2019 International Joint Conference on Neural Networks -- IJCNN'19, 2019
Lukas Fleckenstein, Sebastian Kauschke and Johannes Fürnkranz, [TO APPEAR] Beta Distribution Drift Detection for Adaptive Classifiers, in: Proceedings of the 2019 European Symposium on Artificial Neural Networks -- ESANN'19, 2019
2018
Sebastian Kauschke and Johannes Fürnkranz, Batchwise Patching of Classifiers, in: Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI-18), pages 3374--3381, 2018
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Sebastian Kauschke, Max Mühlhäuser and Johannes Fürnkranz, Leveraging Reproduction-Error Representations for Multi-Instance Classi cation, in: Proceedings of the 21st International Conference on Discovery Science - DS'18, Limassol, Cyprus, pages 83-95, Springer Nature Switzerland AG, 2018
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Jens Heuschkel and Sebastian Kauschke, More Data Matters: Improving CGM Prediction via Ubiquitous Data and Deep Learning, in: Proceedings of the 3rd International Workshop on Ubiquitous Personal Assistance (co-located with Ubicomp), pages 1 -- 8, 2018
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Sebastian Kauschke, Max Mühlhäuser and Johannes Fürnkranz, Towards Semi-Supervised Classification of Event Streams via Denoising Autoencoders, in: Proceedings of the 17th IEEE International Conference on Machine Learning and Applications (ICMLA-18), pages 131--136, IEEE, 2018
Christian Meurisch, Philipp M. Scholl, Usman Naeem, Veljko Pejovic, Florian Müller, Elena Di Lascio, Pei-Yi (Patricia) Kuo, Sebastian Kauschke, Muhammad Awais Azam and Max Mühlhäuser, UPA18: 3rd International Workshop on Ubiquitous Personal Assistance, in: Proceedings of the 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp): Adjunct Publication, ACM, 2018
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2016
Sebastian Kauschke, Johannes Fürnkranz and Frederik Janssen, Predicting Cargo Train Failures: A Machine Learning Approach for a Lightweight Prototype, in: Proceedings of the 19th International Conference on Discovery Science (DS-16), Bari, Italy, pages 151--166, Springer-Verlag, 2016
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2015
Sebastian Kauschke, Frederik Janssen and Immanuel Schweizer, On the Challenges of Real World Data in Predictive Maintenance Scenarios: A Railway Application, in: Proceedings of the LWA 2015 Workshops: KDML, FGWM, IR, and FGDB, Trier, Germany, October 7-9, 2015., pages 121-132, CEUR Workshop Proceedings, 2015
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2014
Sebastian Kauschke, Immanuel Schweizer, Michael Fiebrig and Frederik Janssen, Learning to Predict Component Failures in Trains, in: Proceedings of the 16th LWA Workshops: KDML, IR and FGWM, pages 71--82, CEUR Workshop Proceedings, 2014
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