Daniel Kottke - RankMe

39 papers A 2B 11Journal 11Unranked 7

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	Efficient Bayesian Updates for Deep Active Learning via Laplace Approximations. ECML/PKDD (2) Denis Huseljic, Marek Herde, Lukas Rauch, Paul Hahn, Zhixin Huang, Daniel Kottke, Stephan Vogt, Bernhard Sick
2023	J	`jnl`	Active Label Refinement for Semantic Segmentation of Satellite Images. CoRR Tuan Pham Minh, Jayan Wijesingha, Daniel Kottke, Marek Herde, Denis Huseljic, Bernhard Sick, Michael Wachendorf, Thomas Esch
2023	B	`conf`	Exploring the Potential of Optimal Active Learning via a Non-myopic Oracle Policy. DS Christoph Sandrock, Marek Herde, Daniel Kottke, Bernhard Sick
2022	—	`conf`	A Stopping Criterion for Transductive Active Learning. ECML/PKDD (4) Daniel Kottke, Christoph Sandrock, Georg Krempl, Bernhard Sick
2022	J	`jnl`	Efficient SVDD sampling with approximation guarantees for the decision boundary. Mach. Learn. Adrian Englhardt, Holger Trittenbach, Daniel Kottke, Bernhard Sick, Klemens Böhm
2022	J	`jnl`	Fast Bayesian Updates for Deep Learning with a Use Case in Active Learning. CoRR Marek Herde, Zhixin Huang, Denis Huseljic, Daniel Kottke, Stephan Vogt, Bernhard Sick
2022	—	`ed.`	Proceedings of the Workshop on Interactive Adaptive Learning (IAL 2021) co-located with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2021), Bilbao, Spain, September 13, 2021. IAL@PKDD/ECML Georg Krempl, Vincent Lemaire, Daniel Kottke, Andreas Holzinger, Barbara Hammer
2022	—	`ed.`	Proceedings of the Workshop on Interactive Adaptive Learning co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2022), Grenoble, France, September 23, 2022. IAL@PKDD/ECML Daniel Kottke, Georg Krempl, Andreas Holzinger, Barbara Hammer
2022	J	`jnl`	Stream-based active learning for sliding windows under the influence of verification latency. Mach. Learn. Tuan Pham, Daniel Kottke, Georg Krempl, Bernhard Sick
2021	—	`—`	A holistic, decision-theoretic framework for pool-based active learning. Daniel Kottke
2021	J	`jnl`	ACE: A Novel Approach for the Statistical Analysis of Pairwise Connectivity. CoRR Georg Krempl, Daniel Kottke, Tuan Pham Minh
2021	—	`ch.`	Ein holistischer Ansatz für Pool-basiertes Aktives Lernen. Ausgezeichnete Informatikdissertationen Daniel Kottke
2021	J	`jnl`	Probabilistic Active Learning for Active Class Selection. CoRR Daniel Kottke, Georg Krempl, Marianne Stecklina, Cornelius Styp von Rekowski, Tim Sabsch, Tuan Pham Minh, Matthias Deliano, Myra Spiliopoulou, Bernhard Sick
2021	B	`conf`	Statistical Analysis of Pairwise Connectivity. DS Georg Krempl, Daniel Kottke, Tuan Pham
2021	J	`jnl`	Toward optimal probabilistic active learning using a Bayesian approach. Mach. Learn. Daniel Kottke, Marek Herde, Christoph Sandrock, Denis Huseljic, Georg Krempl, Bernhard Sick
2020	J	`jnl`	Efficient SVDD Sampling with Approximation Guarantees for the Decision Boundary. CoRR Adrian Englhardt, Holger Trittenbach, Daniel Kottke, Bernhard Sick, Klemens Böhm
2020	B	`conf`	Improving Self-Adaptation For Multi-Sensor Activity Recognition with Active Learning. IJCNN Tuan Pham Minh, Daniel Kottke, Anna Tsarenko, Christian Gruhl, Bernhard Sick
2020	B	`conf`	Multi-Annotator Probabilistic Active Learning. ICPR Marek Herde, Daniel Kottke, Denis Huseljic, Bernhard Sick
2020	—	`ed.`	Proceedings of the Workshop on Interactive Adaptive Learning co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2020), Ghent, Belgium, September 14th, 2020. IAL@PKDD/ECML Daniel Kottke, Georg Krempl, Vincent Lemaire, Andreas Holzinger, Adrian Calma
2020	B	`conf`	Separation of Aleatoric and Epistemic Uncertainty in Deterministic Deep Neural Networks. ICPR Denis Huseljic, Bernhard Sick, Marek Herde, Daniel Kottke
2020	J	`jnl`	Toward Optimal Probabilistic Active Learning Using a Bayesian Approach. CoRR Daniel Kottke, Marek Herde, Christoph Sandrock, Denis Huseljic, Georg Krempl, Bernhard Sick
2019	B	`conf`	Combining Self-reported Confidences from Uncertain Annotators to Improve Label Quality. IJCNN Christoph Sandrock, Marek Herde, Adrian Calma, Daniel Kottke, Bernhard Sick
2019	J	`jnl`	Limitations of Assessing Active Learning Performance at Runtime. CoRR Daniel Kottke, Jim Schellinger, Denis Huseljic, Bernhard Sick
2018	B	`conf`	Active Learning With Realistic Data - A Case Study. IJCNN Adrian Calma, Moritz Stolz, Daniel Kottke, Sven Tomforde, Bernhard Sick
2018	B	`conf`	Active Sorting - An Efficient Training of a Sorting Robot with Active Learning Techniques. IJCNN Marek Herde, Daniel Kottke, Adrian Calma, Maarten Bieshaar, Stephan Deist, Bernhard Sick
2018	—	`ed.`	Proceedings of the Workshop on Interactive Adaptive Learning co-located with European Conference on Machine Learning (ECML 2018) and Principles and Practice of Knowledge Discovery in Databases (PKDD 2018), Dublin, Ireland, September 10th, 2018. IAL@PKDD/ECML Georg Krempl, Vincent Lemaire, Daniel Kottke, Adrian Calma, Andreas Holzinger, Robi Polikar, Bernhard Sick
2018	B	`conf`	The Other Human in The Loop - A Pilot Study to Find Selection Strategies for Active Learning. IJCNN Daniel Kottke, Adrian Calma, Denis Huseljic, Christoph Sandrock, George Kachergis, Bernhard Sick
2017	—	`conf`	Challenges of Reliable, Realistic and Comparable Active Learning Evaluation. IAL@PKDD/ECML Daniel Kottke, Adrian Calma, Denis Huseljic, Georg Krempl, Bernhard Sick
2017	—	`conf`	Learning to Learn: Dynamic Runtime Exploitation of Various Knowledge Sources and Machine Learning Paradigms. FAS*W@SASO/ICCAC Adrian Calma, Daniel Kottke, Bernhard Sick, Sven Tomforde
2017	—	`conf`	Probabilistic Active Learning with Structure-Sensitive Kernels. IAL@PKDD/ECML Dominik Lang, Daniel Kottke, Georg Krempl
2017	—	`ed.`	Proceedings of the Workshop and Tutorial on Interactive Adaptive Learning co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2017), Skopje, Macedonia, September 18, 2017. IAL@PKDD/ECML Georg Krempl, Vincent Lemaire, Robi Polikar, Bernhard Sick, Daniel Kottke, Adrian Calma
2016	—	`conf`	Investigating Exploratory Capabilities of Uncertainty Sampling using SVMs in Active Learning. AL@iKNOW Dominik Lang, Daniel Kottke, Georg Krempl, Myra Spiliopoulou
2016	A	`conf`	Multi-Class Probabilistic Active Learning. ECAI Daniel Kottke, Georg Krempl, Dominik Lang, Johannes Teschner, Myra Spiliopoulou
2016	—	`ed.`	Proceedings of the Workshop on Active Learning: Applications, Foundations and Emerging Trends co-located with International Conference on Knowledge Technologies and Data-driven Business (i-KNOW 2016), Graz, Austria, October 18, 2016. AL@iKNOW Georg Krempl, Vincent Lemaire, Edwin Lughofer, Daniel Kottke
2015	—	`conf`	Data-Driven Spine Detection for Multi-Sequence MRI. Bildverarbeitung für die Medizin Daniel Kottke, Gino Gulamhussene, Klaus D. Tönnies
2015	J	`jnl`	Optimised probabilistic active learning (OPAL) - For fast, non-myopic, cost-sensitive active classification. Mach. Learn. Georg Krempl, Daniel Kottke, Vincent Lemaire
2015	B	`conf`	Probabilistic Active Learning in Datastreams. IDA Daniel Kottke, Georg Krempl, Myra Spiliopoulou
2014	A	`conf`	Probabilistic Active Learning: A Short Proposition. ECAI Georg Krempl, Daniel Kottke, Myra Spiliopoulou
2014	B	`conf`	Probabilistic Active Learning: Towards Combining Versatility, Optimality and Efficiency. Discovery Science Georg Krempl, Daniel Kottke, Myra Spiliopoulou