Publications

F. Sattler, T. Korjakow, R. Rischke and W. Samek, “FEDAUX: Leveraging Unlabeled Auxiliary Data in Federated Learning” in IEEE Transactions on Neural Networks and Learning Systems, Dec. 2021.

L. Witt, U. Zafar, K. Shen, F. Sattler, D. Li, W. Samek, “Reward-Based 1-bit Compressed Federated Distillation on Blockchain.” in Computer Science, Machine Learning, https://doi.org/10.48550/arXiv.2106.14265, June 2021.

D. Becking, M. Dreyer, W. Samek, K. Müller and S. Lapuschkin, “ECQ $^{x}$ : Explainability-Driven Quantization for Low-Bit and Sparse DNNs” in Holzinger, A., Goebel, R., Fong, R., Moon, T., Müller, KR., Samek, W. (eds) xxAI – Beyond Explainable AI. xxAI 2020. Lecture Notes in Computer Science(), vol 13200. Springer, Cham., Apr. 2022.

F. Sattler, A. Marban, R. Rischke and W. Samek, “CFD: Communication-Efficient Federated Distillation via Soft-Label Quantization and Delta Coding,” in IEEE Transactions on Network Science and Engineering, May 2022.

S. Ede, S. Baghdadlian, L. Weber, A. Nguyen, D. Zanca, W. Samek and S. Lapuschkin, “Explain to Not Forget: Defending Against Catastrophic Forgetting with XAI.” in Holzinger, A., Kieseberg, P., Tjoa, A.M., Weippl, E. (eds) Machine Learning and Knowledge Extraction. CD-MAKE 2022. Lecture Notes in Computer Science, vol 13480. Springer, Cham., Aug. 2022.

A. Barger, L. Funaro, G. Laventman, H. Meir, D. Moshkovich, S. Natarajan, Y. Tock. “Orion: A Centralized Blockchain Database with Multi-Party Data Access Control” in IEEE International Conference on Blockchain and Cryptocurrency (ICBC), Dubai, United Arab Emirates, 2023, pp. 1-9, doi: 10.1109/ICBC56567.2023.10174914.

K. Krüger, H. Gäbler, A. Gavrielides, E. Symeou, Ph. Philippou, G. Margetis, A. Paradell Bondia, “Online Media Innovations in the Service of Transport and Logistics 4.0: a 5G Paradigm” in EuCNC & 6G summit 2023, Sweden.

Margetis, G. et al. (2023). “Visual Summarisations for Computer-Assisted Live Color Casting and Direction in League of Legends“. In: Fang, X. (eds) HCI in Games. HCII 2023. Lecture Notes in Computer Science, vol 14046. Springer, Cham. https://doi.org/10.1007/978-3-031-35930-9_10

David Neumann, Andreas Lutz, Karsten Müller, and Wojciech Samek, ‘A Privacy Preserving System for Movie Recommendations Using Federated Learning’ ACM Trans. Recomm. Syst. 2023, https://doi.org/10.1145/3634686