2016

Juliana Alves Pereira, Pawel Matuszyk, Sebastian Krieter, Myra Spiliopoulou, and Gunter Saake. A feature-based personalized recommender system for product-line configuration. In Bernd Fischer, and Ina Schaefer (Eds.), Proceedings of the 2016 ACM SIGPLAN International Conference on Generative Programming: Concepts and Experiences, GPCE 2016, 120-131, ACM, 2016. URL

Benjamin Bergner, and Georg Krempl. Active Subtopic Detection in Multitopic Data. In Georg Krempl, Vincent Lemaire, Edwin Lughofer, and Daniel Kottke (Eds.), Proc. of the IKNOW-Workshop on Active Learning: Applications, Foundations and Emerging Trends, CEUR Workshop Proceedings, 2016. URL

Pawel Matuszyk, Rene Tatua Castillo, Daniel Kottke, and Myra Spiliopoulou. A Comparative Study on Hyperparameter Optimization for Recommender Systems. In Elisabeth Lex, Roman Kern, Alexander Felfernig, Kris Jack, Dominik Kowald, and Emanuel Lacic (Eds.), Workshop on Recommender Systems and Big Data Analytics (RS-BDA'16) @ iKNOW 2016, 2016. URL

Marianne Stecklina, Tuan Phan Minh, Tim Sabsch, Cornelius Styp von Rekowski, Daniel Kottke, Georg Krempl, Matthias Deliano, and Myra Spiliopoulou. Active Selection of Difficult Classes. Tagung der Deutschen Arbeitsgemeinschaft Statistik (DAGSTAT), 2016. URL

Georg Krempl, Vincent Lemaire, Edwin Lughofer, and Daniel Kottke. Tutorial on Active Learning: Applications, Foundations and Emerging Trends. 2016.

Georg Krempl, and Vera Hofer. Learning from monitoring unlabelled data under large verification latency. In Iris Pigeot, and Eyke Hüllermeier (Eds.), Joint Statistical Meeting DAGStat2016, Big Data and Data Science Track, 2016.

Michael Hanke, Nico Adelhöfer, Daniel Kottke, Vittorio Iacovella, Ayan Sengupta, Falko R. Kaule, Roland Nigbur, Alexander Q. Waite, Florian Baumgartner, and Jörg Stadler. A studyforrest extension, simultaneous fMRI and eye gaze recordings during prolonged natural stimulation. Scientific Data, (3)160092Nature Publishing Group, October 2016. URL

Dominik Lang, Daniel Kottke, Georg Krempl, and Myra Spiliopoulou. Investigating Exploratory Capabilities of Uncertainty Sampling using SVMs in Active Learning. In Georg Krempl, Vincent Lemaire, Edwin Lughofer, and Daniel Kottke (Eds.), Active Learning: Applications, Foundations and Emerging Trends @iKnow 2016, 25-34, 2016. URL

Workshop on Active Learning: Applications, Foundations and Emerging Trends. In Georg Krempl, Vincent Lemaire, Edwin Lughofer, and Daniel Kottke (Eds.), CEUR Workshop Proceedings, (1707)Aachen University, Aachen, 2016. URL

Uli Niemann, Myra Spiliopoulou, Fred Samland, Thorsten Szczepanski, Jens Grützner, Antao Ming, Juliane Kellersmann, Jan Malanowski, Silke Klose, and Peter R. Mertens. Learning Pressure Patterns for Patients with Diabetic Foot Syndrome. Proc. of the 29th IEEE Int. Symposium on Computer-Based Medical Systems (CBMS16), IEEE, Dublin, Ireland and Belfast, Northern Ireland, June 2016.

Georg Krempl. Kombiniert Lernen - Effizient und effektiv Lehren. In Philipp Pohlenz (Eds.), Best practice in teaching, Tag der Lehre 2016, Magdeburg University., Jun 22, 2016. URL

Georg Krempl. Profilierung interdisziplinärer Nachwuchswissenschaftler -- Profilstudium und Summerschool Lernende Systeme / Biocomputing. In Barbara Paech (Eds.), Best practices in teaching, Deutscher Fakultätentag Informatik, 2016. URL

Tommy Hielscher, Myra Spiliopoulou, Henry Völzke, and Jens-Peter Kühn. Identifying relevant features for a multi-factorial disorder with constraint-based subspace clustering. Proc. of the 29th IEEE Int. Symposium on Computer-Based Medical Systems (CBMS16), IEEE, Dublin, Ireland and Belfast, Northern Ireland, 2016.

Daniel Kottke, Georg Krempl, Dominik Lang, Johannes Teschner, and Myra Spiliopoulou. Multi-Class Probabilistic Active Learning. In Gal A. Kaminka, Maria Fox, Paolo Bouquet, Eyke Hüllermeier, Virginia Dignum, Frank Dignum, and Frank van Harmelen (Eds.), ECAI, (285):586-594, IOS Press, 2016. URL

Daniel Kottke, Georg Krempl, and Myra Spiliopoulou. Temporal Aspects of Stream Active Learning. Tagung der Deutschen Arbeitsgemeinschaft Statistik (DAGSTAT), 2016. URL

Georg Krempl, Daniel Kottke, Tuan Pham Minh, Fabian Göcke, Sebastian Hesse, Tino Reising, and Myra Spiliopoulou. Inferring Delayed Neural Network Connections. In John Aston, Claudia Kirch, and Hernando Ombao (Eds.), Conference on Novel Statistical Methods in Neuroscience (NeuroStat 2016), 2016.

Anita Hrubos, David Bodnar, Georg Krempl, and Myra Spiliopoulou. Prediction-Induced Drift as New Form of Drift. In Iris Pigeot, and Eyke Hüllermeier (Eds.), Joint Statistical Meeting DAGStat2016, Big Data and Data Science Track, 2016.

Uli Niemann, Myra Spiliopoulou, Thorsten Szczepanski, Fred Samland, Jens Grützner, Dominik Senk, Antao Ming, Juliane Kellersmann, Jan Malanowski, Silke Klose, and Peter R. Mertens. Comparative Clustering of Plantar Pressure Distributions in Diabetics with Polyneuropathy May Be Applied to Reveal Inappropriate Biomechanical Stress. PLoS ONE, (11)8:1-12, Public Library of Science, August 2016. URL

Daniel Kottke, Georg Krempl, Marianne Stecklina, Cornelius Styp von Rekowski, Tim Sabsch, Tuan Pham Minh, Matthias Deliano, Myra Spiliopoulou, and Bernhard Sick. Probabilistic Active Learning for Active Class Selection. In Kory Mathewson, Kaushik Subramanian, and Robert Loftin (Eds.), Proc. of the NIPS Workshop on the Future of Interactive Learning Machines, 2016. URL

Georg Krempl, and Marianne Stecklina. On Temporal Density Extrapolation Using Kernels. In Miłosz Kadziński (Eds.), 28th European Conference on Operational Research (EURO 2016), 2016. URL