Florian Kalinke

According to our database, Florian Kalinke authored at least 15 papers between 2021 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Robust partial-label learning by leveraging class activation values.

Tobias Fuchs, Florian Kalinke

Mach. Learn., August, 2025

Optimal Online Change Detection via Random Fourier Features.

Florian Kalinke, Shakeel Gavioli-Akilagun

CoRR, May, 2025

Maximum Mean Discrepancy on Exponential Windows for Online Change Detection.

Florian Kalinke, Marco Heyden, Georg Gntuni, Edouard Fouché, Klemens Böhm

Trans. Mach. Learn. Res., 2025

Partial-Label Learning with a Reject Option.

Tobias Fuchs, Florian Kalinke, Klemens Böhm

Trans. Mach. Learn. Res., 2025

Partial-Label Learning with Conformal Candidate Cleaning.

Tobias Fuchs, Florian Kalinke

Proceedings of the Conference on Uncertainty in Artificial Intelligence, 2025

Nyström Kernel Stein Discrepancy.

Florian Kalinke, Zoltán Szabó, Bharath K. Sriperumbudur

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2025

2024

Adaptive Bernstein change detector for high-dimensional data streams.

Marco Heyden, Edouard Fouché, Vadim Arzamasov, Tanja Fenn, Florian Kalinke, Klemens Böhm

Data Min. Knowl. Discov., May, 2024

Uncertainty-Aware Partial-Label Learning.

Tobias Fuchs, Florian Kalinke, Klemens Böhm

CoRR, 2024

The Minimax Rate of HSIC Estimation for Translation-Invariant Kernels.

Florian Kalinke, Zoltán Szabó

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

Nyström M-Hilbert-Schmidt independence criterion.

Florian Kalinke, Zoltán Szabó

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Multi-kernel Times Series Outlier Detection.

Florian Kalinke, Edouard Fouché, Haiko Thiessen, Klemens Böhm

Proceedings of the Discovery Science - 26th International Conference, 2023

2022

Scalable Online Change Detection for High-dimensional Data Streams.

Florian Kalinke, Marco Heyden, Edouard Fouché, Klemens Böhm

CoRR, 2022

2021

Efficient subspace search in data streams.

Edouard Fouché, Florian Kalinke, Klemens Böhm

Inf. Syst., 2021

A framework for dependency estimation in heterogeneous data streams.

Edouard Fouché, Alan Mazankiewicz, Florian Kalinke, Klemens Böhm

Distributed Parallel Databases, 2021

An Evaluation of NILM Approaches on Industrial Energy-Consumption Data.

Florian Kalinke, Pawel Bielski, Snigdha Singh, Edouard Fouché, Klemens Böhm

Proceedings of the e-Energy '21: The Twelfth ACM International Conference on Future Energy Systems, Virtual Event, Torino, Italy, 28 June, 2021