D. Kottke

发表

Optimised probabilistic active learning ( OPAL ) For fast , non-myopic , cost-sensitive active classification

V. Lemaire, G. Krempl, D. Kottke, 2015 .

Stream-based active learning for sliding windows under the influence of verification latency

B. Sick, G. Krempl, D. Kottke, 2021, Machine Learning.

A Stopping Criterion for Transductive Active Learning

B. Sick, G. Krempl, D. Kottke, 2022, ECML/PKDD.

Fast Bayesian Updates for Deep Learning with a Use Case in Active Learning

S. Vogt, B. Sick, D. Kottke, 2022, ArXiv.

Workshop on Interactive Adaptive Learning

R. Polikar, V. Lemaire, B. Sick, 2018 .

A studyforrest extension, simultaneous fMRI and eye gaze recordings during prolonged natural stimulation

Michael Hanke, Daniel Kottke, Florian Baumgartner, 2016, Scientific Data.

Multi-Annotator Probabilistic Active Learning

Bernhard Sick, Daniel Kottke, Marek Herde, 2021, 2020 25th International Conference on Pattern Recognition (ICPR).

Toward optimal probabilistic active learning using a Bayesian approach pdf

Bernhard Sick, Georg Krempl, Daniel Kottke, 2020, Machine Learning.

Separation of Aleatoric and Epistemic Uncertainty in Deterministic Deep Neural Networks

Bernhard Sick, Daniel Kottke, Marek Herde, 2021, 2020 25th International Conference on Pattern Recognition (ICPR).

Active Sorting – An Efficient Training of a Sorting Robot with Active Learning Techniques

Bernhard Sick, Adrian Calma, Daniel Kottke, 2018, 2018 International Joint Conference on Neural Networks (IJCNN).

Challenges of Reliable, Realistic and Comparable Active Learning Evaluation

Bernhard Sick, Adrian Calma, Georg Krempl, 2017, IAL@PKDD/ECML.

Improving Self-Adaptation For Multi-Sensor Activity Recognition with Active Learning

Bernhard Sick, Daniel Kottke, Christian Gruhl, 2020, 2020 International Joint Conference on Neural Networks (IJCNN).

Learning to Learn: Dynamic Runtime Exploitation of Various Knowledge Sources and Machine Learning Paradigms

Sven Tomforde, Bernhard Sick, Adrian Calma, 2017, 2017 IEEE 2nd International Workshops on Foundations and Applications of Self* Systems (FAS*W).

Simultaneous fMRI and eye gaze recordings during prolonged natural stimulation - a studyforrest extension

Michael Hanke, Ayan Sengupta, Daniel Kottke, 2016, bioRxiv.

Active Learning With Realistic Data - A Case Study

Sven Tomforde, Bernhard Sick, Adrian Calma, 2018, 2018 International Joint Conference on Neural Networks (IJCNN).

Combining Self-reported Confidences from Uncertain Annotators to Improve Label Quality

Bernhard Sick, Adrian Calma, Daniel Kottke, 2019, 2019 International Joint Conference on Neural Networks (IJCNN).

Detection of irregular patterns of myocardial contraction in patients with hypertensive heart disease: a two-dimensional ultrasound speckle tracking study

T. Edvardsen, H. Figulla, C. Jung, 2011, Journal of hypertension.

Probabilistic Active Learning for Active Class Selection pdf

Myra Spiliopoulou, Bernhard Sick, Tim Sabsch, 2021, ArXiv.

Probabilistic Active Learning: Towards Combining Versatility, Optimality and Efficiency

Myra Spiliopoulou, Georg Krempl, Daniel Kottke, 2014, Discovery Science.

Probabilistic Active Learning: A Short Proposition

Myra Spiliopoulou, Georg Krempl, Daniel Kottke, 2014, ECAI.

Statistical Analysis of Pairwise Connectivity

Georg Krempl, Daniel Kottke, Tuan Pham, 2021, IFIP Working Conference on Database Semantics.

ACE: A Novel Approach for the Statistical Analysis of Pairwise Connectivity pdf

Georg Krempl, Daniel Kottke, Tuan Pham Minh, 2021, ArXiv.

Limitations of Assessing Active Learning Performance at Runtime pdf

Bernhard Sick, Daniel Kottke, Denis Huseljic, 2019, ArXiv.

Towards Proactive Health-Enabling Living Environments: Simulation-Based Study and Research Challenges

Reinhold Haux, Sven Tomforde, Ali Sunyaev, 2018 .

scikit-activeml: A Library and Toolbox for Active Learning Algorithms

Bernhard Sick, Daniel Kottke, Marek Herde, 2021 .

Automated Active Learning with a Robot

Bernhard Sick, Adrian Calma, Daniel Kottke, 2018 .