Robust and communication-efficient federated learning from non-iid data F Sattler, S Wiedemann, KR Müller, W Samek IEEE transactions on neural networks and learning systems 31 (9), 3400-3413, 2019 | 196 | 2019 |
Sparse binary compression: Towards distributed deep learning with minimal communication F Sattler, S Wiedemann, KR Müller, W Samek 2019 International Joint Conference on Neural Networks (IJCNN), 1-8, 2019 | 61 | 2019 |
Clustered federated learning: Model-agnostic distributed multitask optimization under privacy constraints F Sattler, KR Müller, W Samek IEEE Transactions on Neural Networks and Learning Systems, 2020 | 42 | 2020 |
Risk estimation of SARS-CoV-2 transmission from bluetooth low energy measurements F Sattler, J Ma, P Wagner, D Neumann, M Wenzel, R Schäfer, W Samek, ... NPJ digital medicine 3 (1), 1-4, 2020 | 12 | 2020 |
On the byzantine robustness of clustered federated learning F Sattler, KR Müller, T Wiegand, W Samek ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 6 | 2020 |
Trends and advancements in deep neural network communication F Sattler, T Wiegand, W Samek arXiv preprint arXiv:2003.03320, 2020 | 2 | 2020 |
Deepcabac: Plug & Play Compression of Neural Network Weights and Weight Updates D Neumann, F Sattler, H Kirchhoffer, S Wiedemann, K Müller, H Schwarz, ... 2020 IEEE International Conference on Image Processing (ICIP), 21-25, 2020 | 1 | 2020 |
Black Box Optimization using Recurrent Neural Networks P Chormai, F Sattler, R Holca-Lammare | 1 | 2017 |
Concepts for distributed learning of neural networks and/or transmission of parameterization updates therefor W SAMEK, S WIEDEMANN, F SATTLER, KR Müller, T Wiegand US Patent App. 17/096,887, 2021 | | 2021 |
FedAUX: Leveraging Unlabeled Auxiliary Data in Federated Learning F Sattler, T Korjakow, R Rischke, W Samek arXiv preprint arXiv:2102.02514, 2021 | | 2021 |
Communication-Efficient Federated Distillation F Sattler, A Marban, R Rischke, W Samek arXiv preprint arXiv:2012.00632, 2020 | | 2020 |
Clustered Federated Learning F Sattler, KR Müller, W Samek | | |