Daniel Kottke
Daniel Kottke
Research Assistant, Kassel University
Verifisert e-postadresse på uni-kassel.de - Startside
Tittel
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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
37*2016
Optimised probabilistic active learning (OPAL)
G Krempl, D Kottke, V Lemaire
Machine Learning 100 (2-3), 449-476, 2015
342015
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
20*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
142017
Probabilistic active learning in datastreams
D Kottke, G Krempl, M Spiliopoulou
International Symposium on Intelligent Data Analysis, 145-157, 2015
132015
Probabilistic active learning: Towards combining versatility, optimality and efficiency
G Krempl, D Kottke, M Spiliopoulou
International Conference on Discovery Science, 168-179, 2014
132014
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
102017
A comparative study on hyperparameter optimization for recommender systems
P Matuszyk, RT Castillo, D Kottke, M Spiliopoulou
Proceedings of the meeting of the Workshop on rcommender Systems and Big …, 2016
82016
Probabilistic Active Learning: A Short Proposition.
G Krempl, D Kottke, M Spiliopoulou
ECAI, 1049-1050, 2014
52014
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
32018
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
32016
Limitations of assessing active learning performance at runtime
D Kottke, J Schellinger, D Huseljic, B Sick
arXiv preprint arXiv:1901.10338, 2019
22019
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
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
12018
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
12016
On Optimising Sample Selection in Credit Scoring with Active Learning
G Krempl, D Kottke
Credit Scoring and Credit Control XV, 2, 0
1
Toward Optimal Probabilistic Active Learning Using a Bayesian Approach
D Kottke, M Herde, C Sandrock, D Huseljic, G Krempl, B Sick
arXiv preprint arXiv:2006.01732, 2020
2020
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
2019
Automated Active Learning with a Robot
K Scharei, M Herde, M Bieshaar, A Calma, D Kottke, B Sick
Archives of Data Science, Series A (Online First) 5 (1), 16, 2018
2018
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Artikler 1–20