Adaptive multi-modal positive semi-definite and indefinite kernel fusion for binary classification. - Maximilian Münch; Christoph Raab; Simon Heilig; Manuel Röder; Frank-Michael Schleif (ESANN, 2022)

Domain adversarial tangent subspace alignment for explainable domain adaptation. - Christoph Raab; Manuel Röder; Frank-Michael Schleif (Neurocomputing, 2022)

Unlocking the Potential of Non-PSD Kernel Matrices: A Polar Decomposition-based Transformation for Improved Prediction Models. - Maximilian Münch; Manuel Röder; Frank-Michael Schleif (CIKM, 2023)

Efficient Cross-Domain Federated Learning by MixStyle Approximation. - Manuel Röder; Leon Heller; Maximilian Münch; Frank-Michael Schleif (CoRR, 2023)

Static and adaptive subspace information fusion for indefinite heterogeneous proximity data. - Maximilian Münch; Manuel Röder; Simon Heilig; Christoph Raab; Frank-Michael Schleif (Neurocomputing, 2023)

Sparse Uncertainty-Informed Sampling from Federated Streaming Data. - Manuel Röder; Frank-Michael Schleif (ESANN, 2024)

Deep Transfer Hashing for Adaptive Learning on Federated Streaming Data. - Manuel Röder; Frank-Michael Schleif (IAL@PKDD/ECML, 2024)

Crossing Domain Borders with Federated Few-Shot Adaptation. - Manuel Röder; Maximilian Münch; Christoph Raab; Frank-Michael Schleif (ICPRAM, 2024)

Domain Borders Are There to Be Crossed With Federated Few-Shot Adaptation. - Manuel Röder; Christoph Raab; Frank-Michael Schleif (CoRR, 2025)