| 2026 | ESANN | Polarizing Kernels: A Definite Approach to Clustering with Indefinite Similarities. | Frank-Michael Schleif, Manuel Rder, Maximilian Mnch, Peter Preinesberger |
| 2025 | ESANN | Resource-Aware Cooperation in Federated Learning. | Manuel Rder, Fabian Geiger, Frank-Michael Schleif |
| 2025 | IJCNN | Driving Cooperation in Federated Learning via Evolutionary Game Theory. | Manuel Rder, Fabian Geiger, Frank-Michael Schleif |
| 2025 | IDEAL | On the Use of Smooth-L1 Approximation in Echo State Networks for Sparse and Efficient Temporal Modeling. | Gengcheng Lyu, Manuel Rder, Frank-Michael Schleif |
| 2024 | ESANN | Sparse Uncertainty-Informed Sampling from Federated Streaming Data. | Manuel Rder, Frank-Michael Schleif |
| 2024 | ICPRAM | Crossing Domain Borders with Federated Few-Shot Adaptation. | Manuel Rder, Maximilian Mnch, Christoph Raab, Frank-Michael Schleif |
| 2023 | CIKM | Unlocking the Potential of Non-PSD Kernel Matrices: A Polar Decomposition-based Transformation for Improved Prediction Models. | Maximilian Mnch, Manuel Rder, Frank-Michael Schleif |
| 2022 | ESANN | Adaptive multi-modal positive semi-definite and indefinite kernel fusion for binary classification. | Maximilian Mnch, Christoph Raab, Simon Heilig, Manuel Rder, Frank-Michael Schleif |