Daniel Kottke
Daniel Kottke
Researcher, Kassel University
Verified email at uni-kassel.de - Homepage
Title
Cited by
Cited by
Year
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
54*2016
Optimised probabilistic active learning (OPAL)
G Krempl, D Kottke, V Lemaire
Machine Learning 100 (2), 449-476, 2015
432015
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
242016
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
222017
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
212017
Probabilistic active learning: Towards combining versatility, optimality and efficiency
G Krempl, D Kottke, M Spiliopoulou
International Conference on Discovery Science, 168-179, 2014
162014
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 (RS-BDA'16), 13, 2016
152016
Probabilistic active learning in datastreams
D Kottke, G Krempl, M Spiliopoulou
International Symposium on Intelligent Data Analysis, 145-157, 2015
152015
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
7*2016
Toward optimal probabilistic active learning using a bayesian approach
D Kottke, M Herde, C Sandrock, D Huseljic, G Krempl, B Sick
Machine Learning, 1-33, 2021
62021
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
62018
Limitations of assessing active learning performance at runtime
D Kottke, J Schellinger, D Huseljic, B Sick
arXiv preprint arXiv:1901.10338, 2019
52019
A studyforrest extension, simultaneous fMRI and eye gaze recordings during prolonged natural stimulation. Scientific Data, 3, 160092
M Hanke, N Adelhöfer, D Kottke, V Iacovella, A Sengupta, FR Kaule, ...
52016
Probabilistic active learning: A short proposition
G Krempl, D Kottke, M Spiliopoulou
ECAI 2014, 1049-1050, 2014
52014
Separation of Aleatoric and Epistemic Uncertainty in Deterministic Deep Neural Networks
D Huseljic, B Sick, M Herde, D Kottke
2020 25th International Conference on Pattern Recognition (ICPR), 9172-9179, 2021
22021
Multi-Annotator Probabilistic Active Learning
M Herde, D Kottke, D Huseljic, B Sick
2020 25th International Conference on Pattern Recognition (ICPR), 10281-10288, 2021
22021
Combining Self-reported Confidences from Uncertain Annotators to Improve Label Quality
C Sandrock, M Herde, A Calma, D Kottke, B Sick
2019 International Joint Conference on Neural Networks (IJCNN), 1-8, 2019
22019
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
22018
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
22018
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
22018
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