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Daniel Kottke
Daniel Kottke
Researcher, Kassel University
Verified email at uni-kassel.de - Homepage
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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
972016
Optimised probabilistic active learning (OPAL) for fast, non-myopic, cost-sensitive active classification
G Krempl, D Kottke, V Lemaire
Machine Learning 100, 449-476, 2015
552015
Transfer learning for time series anomaly detection
V Vercruyssen, W Meert, J Davis
Proceedings of the Workshop and Tutorial on Interactive Adaptive Learning …, 2017
412017
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
382017
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
332016
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
292017
Probabilistic active learning in datastreams
D Kottke, G Krempl, M Spiliopoulou
Advances in Intelligent Data Analysis XIV: 14th International Symposium, IDA …, 2015
272015
Toward optimal probabilistic active learning using a Bayesian approach
D Kottke, M Herde, C Sandrock, D Huseljic, G Krempl, B Sick
Machine Learning 110 (6), 1199-1231, 2021
232021
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
232021
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).-2016.-Р …, 2016
232016
Probabilistic active learning: Towards combining versatility, optimality and efficiency
G Krempl, D Kottke, M Spiliopoulou
Discovery Science: 17th International Conference, DS 2014, Bled, Slovenia …, 2014
202014
Stream-based active learning for sliding windows under the influence of verification latency
T Pham, D Kottke, G Krempl, B Sick
Machine Learning, 1-26, 2022
172022
Limitations of assessing active learning performance at runtime
D Kottke, J Schellinger, D Huseljic, B Sick
arXiv preprint arXiv:1901.10338, 2019
142019
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
14*2016
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, ...
102016
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
92018
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
82018
Probabilistic active learning: A short proposition
G Krempl, D Kottke, M Spiliopoulou
ECAI 2014, 1049-1050, 2014
72014
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
62021
Multi-annotator probabilistic active learning
M Herde, D Kottke, D Huseljic, B Sick
2020 25th International Conference on Pattern Recognition (ICPR), 10281-10288, 2021
62021
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