| 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 | 538 | 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 32 (8), 3710-3722, 2020 | 207 | 2020 |
| 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 | 106 | 2019 |
| 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 | 37 | 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 | 26 | 2020 |
| Communication-efficient federated distillation F Sattler, A Marban, R Rischke, W Samek arXiv preprint arXiv:2012.00632, 2020 | 12 | 2020 |
| Fedaux: Leveraging unlabeled auxiliary data in federated learning F Sattler, T Korjakow, R Rischke, W Samek IEEE Transactions on Neural Networks and Learning Systems, 2021 | 9 | 2021 |
| Trends and advancements in deep neural network communication F Sattler, T Wiegand, W Samek arXiv preprint arXiv:2003.03320, 2020 | 8 | 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 | 5 | 2020 |
| CFD: Communication-Efficient Federated Distillation via Soft-Label Quantization and Delta Coding F Sattler, A Marban, R Rischke, W Samek IEEE Transactions on Network Science and Engineering, 2021 | 4 | 2021 |
| Reward-Based 1-bit Compressed Federated Distillation on Blockchain L Witt, U Zafar, KY Shen, F Sattler, D Li, W Samek arXiv preprint arXiv:2106.14265, 2021 | 2 | 2021 |
| Clustered Federated Learning F Sattler, KR Müller, W Samek Proceedings of the NeurIPS’19 Workshop on Federated Learning for Data …, 2019 | 2 | 2019 |
| Black Box Optimization using Recurrent Neural Networks P Chormai, F Sattler, R Holca-Lammare | 1 | 2017 |
| Concepts for federated learning, client classification and training data similarity measurement W Samek, F Sattler, T Wiegand, KR Müller US Patent App. 17/526,739, 2022 | | 2022 |
| 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 |
| Concepts for Efficient, Adaptive and Robust Deep Learning from Distributed Data/Konzepte Für Effizientes, Adaptives und Robustes Trainieren von Tiefen Neuronalen Netzen auf … F Sattler Technische Universitaet Berlin (Germany), 2021 | | 2021 |
| Concepts for efficient, adaptive and robust deep learning from distributed data F Sattler | | 2021 |
Wojciech SamekProfessor at TU Berlin, Head of AI Department at Fraunhofer HHI, BIFOLD FellowVerified email at hhi.fraunhofer.de
