Kamp, Michael

20 publications

ICLR 2026 When Flatness Does (Not) Guarantee Adversarial Robustness Nils Philipp Walter, Linara Adilova, Jilles Vreeken, Michael Kamp

AAAI 2025 Federated Binary Matrix Factorization Using Proximal Optimization Sebastian Dalleiger, Jilles Vreeken, Michael Kamp

NeurIPS 2025 Flatness Is Necessary, Neural Collapse Is Not: Rethinking Generalization via Grokking Ting Han, Linara Adilova, Henning Petzka, Jens Kleesiek, Michael Kamp

AAAI 2025 Little Is Enough: Boosting Privacy by Sharing Only Hard Labels in Federated Semi-Supervised Learning Amr Abourayya, Jens Kleesiek, Kanishka Rao, Erman Ayday, Bharat Rao, Geoffrey I. Webb, Michael Kamp

ICMLW 2024 Landscaping Linear Mode Connectivity Sidak Pal Singh, Linara Adilova, Michael Kamp, Asja Fischer, Bernhard Schölkopf, Thomas Hofmann

ICLR 2024 Layer-Wise Linear Mode Connectivity Linara Adilova, Maksym Andriushchenko, Michael Kamp, Asja Fischer, Martin Jaggi

AISTATS 2024 Orthogonal Gradient Boosting for Simpler Additive Rule Ensembles Fan Yang, Pierre Le Bodic, Michael Kamp, Mario Boley

ICMLW 2023 FAM: Relative Flatness Aware Minimization Linara Adilova, Amr Abourayya, Jianning Li, Amin Dada, Henning Petzka, Jan Egger, Jens Kleesiek, Michael Kamp

ICLR 2023 Federated Learning from Small Datasets Michael Kamp, Jonas Fischer, Jilles Vreeken

AAAI 2023 Information-Theoretic Causal Discovery and Intervention Detection over Multiple Environments Osman Mian, Michael Kamp, Jilles Vreeken

AISTATS 2023 Nothing but Regrets — Privacy-Preserving Federated Causal Discovery Osman Mian, David Kaltenpoth, Michael Kamp, Jilles Vreeken

NeurIPSW 2022 AIMHI: Protecting Sensitive Data Through Federated Co-Training Amr Abourayya, Michael Kamp, Erman Ayday, Jens Kleesiek, Kanishka Rao, Geoffrey I. Webb, Bharat Rao

ICLR 2021 FedBN: Federated Learning on Non-IID Features via Local Batch Normalization Xiaoxiao Li, Meirui Jiang, Xiaofei Zhang, Michael Kamp, Qi Dou

NeurIPS 2021 Relative Flatness and Generalization Henning Petzka, Michael Kamp, Linara Adilova, Cristian Sminchisescu, Mario Boley

ECML-PKDD 2018 Efficient Decentralized Deep Learning by Dynamic Model Averaging Michael Kamp, Linara Adilova, Joachim Sicking, Fabian Hüger, Peter Schlicht, Tim Wirtz, Stefan Wrobel

ECML-PKDD 2017 Co-Regularised Support Vector Regression Katrin Ullrich, Michael Kamp, Thomas Gärtner, Martin Vogt, Stefan Wrobel

NeurIPS 2017 Effective Parallelisation for Machine Learning Michael Kamp, Mario Boley, Olana Missura, Thomas Gärtner

ECML-PKDD 2016 Communication-Efficient Distributed Online Learning with Kernels Michael Kamp, Sebastian Bothe, Mario Boley, Michael Mock

ECML-PKDD 2014 Communication-Efficient Distributed Online Prediction by Dynamic Model Synchronization Michael Kamp, Mario Boley, Daniel Keren, Assaf Schuster, Izchak Sharfman

ECML-PKDD 2013 Privacy-Preserving Mobility Monitoring Using Sketches of Stationary Sensor Readings Michael Kamp, Christine Kopp, Michael Mock, Mario Boley, Michael May