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Kamp, Michael; Fischer, Jonas; Vreeken, Jilles

Federated Learning from Small Datasets (Journal Article)

In: arXiv preprint arXiv:2110.03469, 2022.

(Links | BibTeX | Tags: black-box, black-box parallelization, daisy, daisy-chaining, FedDC, federated learning, small, small datasets)


Linsner, Florian; Adilova, Linara; Däubener, Sina; Kamp, Michael; Fischer, Asja

Approaches to Uncertainty Quantification in Federated Deep Learning (Workshop)

Machine Learning and Principles and Practice of Knowledge Discovery in Databases: International Workshops of ECML PKDD 2021, vol. 2, Springer, 2021.

(Links | BibTeX | Tags: federated learning, uncertainty)

Li, Xiaoxiao; Jiang, Meirui; Zhang, Xiaofei; Kamp, Michael; Dou, Qi

FedBN: Federated Learning on Non-IID Features via Local Batch Normalization (Inproceedings)

In: Proceedings of the 9th International Conference on Learning Representations (ICLR), 2021.

(Abstract | Links | BibTeX | Tags: batch normalization, black-box parallelization, deep learning, federated learning)


Kamp, Michael; Adilova, Linara; Sicking, Joachim; Hüger, Fabian; Schlicht, Peter; Wirtz, Tim; Wrobel, Stefan

Efficient Decentralized Deep Learning by Dynamic Model Averaging (Inproceedings)

In: Machine Learning and Knowledge Discovery in Databases, Springer, 2018.

(Abstract | Links | BibTeX | Tags: decentralized, deep learning, federated learning)


Kamp, Michael; Bothe, Sebastian; Boley, Mario; Mock, Michael

Communication-Efficient Distributed Online Learning with Kernels (Inproceedings)

In: Frasconi, Paolo; Landwehr, Niels; Manco, Giuseppe; Vreeken, Jilles (Ed.): Machine Learning and Knowledge Discovery in Databases, pp. 805–819, Springer International Publishing, 2016.

(Abstract | Links | BibTeX | Tags: communication-efficient, distributed, dynamic averaging, federated learning, kernel methods, parallelization)