Daniel Kottke
Daniel Kottke
Research Assistant, Kassel University
Bestätigte E-Mail-Adresse bei uni-kassel.de - Startseite
Zitiert von
Zitiert von
A studyforrest extension, simultaneous fMRI and eye gaze recordings during prolonged natural stimulation
M Hanke, N Adelhöfer, D Kottke, V Iacovella, A Sengupta, FR Kaule, ...
Scientific data 3 (1), 1-15, 2016
Optimised probabilistic active learning (OPAL)
G Krempl, D Kottke, V Lemaire
Machine Learning 100 (2), 449-476, 2015
Multi-Class Probabilistic Active Learning
D Kottke, G Krempl, D Lang, J Teschner, M Spiliopoulou
Frontiers in Artificial Intelligence and Applications 285, 586-594 (ECAI), 2016
Learning to Learn: Dynamic Runtime Exploitation of Various Knowledge Sources and Machine Learning Paradigms
A Calma, D Kottke, B Sick, S Tomforde
2nd IEEE International Workshops on Foundations and Applications of Self …, 2017
Challenges of Reliable, Realistic and Comparable Active Learning Evaluation
D Kottke, A Calma, D Huseljic, G Krempl, B Sick
Proceedings of the Workshop and Tutorial on Interactive Adaptive Learning …, 2017
Probabilistic active learning: Towards combining versatility, optimality and efficiency
G Krempl, D Kottke, M Spiliopoulou
International Conference on Discovery Science, 168-179, 2014
Probabilistic active learning in datastreams
D Kottke, G Krempl, M Spiliopoulou
International Symposium on Intelligent Data Analysis, 145-157, 2015
A comparative study on hyperparameter optimization for recommender systems
P Matuszyk, RT Castillo, D Kottke, M Spiliopoulou
Workshop on Recommender Systems and Big Data Analytics, 13-21, 2016
Active learning with realistic data-a case study
A Calma, M Stolz, D Kottke, S Tomforde, B Sick
2018 International Joint Conference on Neural Networks (IJCNN), 1-8, 2018
Probabilistic Active Learning for Active Class Selection
D Kottke, G Krempl, M Stecklina, CS von Rekowski, T Sabsch, TP Minh, ...
Future of Interactive Learning Machines Workshop @NIPS 2016, 2016
Probabilistic Active Learning: A Short Proposition.
G Krempl, D Kottke, M Spiliopoulou
ECAI, 1049-1050, 2014
Limitations of assessing active learning performance at runtime
D Kottke, J Schellinger, D Huseljic, B Sick
arXiv preprint arXiv:1901.10338, 2019
The Other Human in The Loop–A Pilot Study to Find Selection Strategies for Active Learning
D Kottke, A Calma, D Huseljic, C Sandrock, G Kachergis, B Sick
2018 International Joint Conference on Neural Networks (IJCNN), 1-8, 2018
Towards proactive health-enabling living environments: Simulation-based study and research challenges
S Tomforde, T Dehling, R Haux, D Huseljic, D Kottke, J Scheerbaum, ...
ARCS Workshop 2018; 31th International Conference on Architecture of …, 2018
Active Sorting–An Efficient Training of a Sorting Robot with Active Learning Techniques
M Herde, D Kottke, A Calma, M Bieshaar, S Deist, B Sick
2018 International Joint Conference on Neural Networks (IJCNN), 1-8, 2018
Investigating Exploratory Capabilities of Uncertainty Sampling using SVMs in Active Learning
D Lang, D Kottke, G Krempl, M Spiliopoulou
Active Learning: Applications, Foundations and Emerging Trends @iKnow 2016, 2016
On Optimising Sample Selection in Credit Scoring with Active Learning
G Krempl, D Kottke
Credit Scoring and Credit Control XV, 2, 0
scikit-activeml: A Library and Toolbox for Active Learning Algorithms
D Kottke, M Herde, TP Minh, A Benz, P Mergard, A Roghman, C Sandrock, ...
Preprints, 2021
Efficient SVDD Sampling with Approximation Guarantees for the Decision Boundary
A Englhardt, H Trittenbach, D Kottke, B Sick, K Böhm
arXiv preprint arXiv:2009.13853, 2020
Improving Self-Adaptation For Multi-Sensor Activity Recognition with Active Learning
TP Minh, D Kottke, A Tsarenko, C Gruhl, B Sick
2020 International Joint Conference on Neural Networks (IJCNN), 1-8, 2020
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