| 2025 | AAAI | 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 |
| 2025 | AAAI | Federated Binary Matrix Factorization Using Proximal Optimization. | Sebastian Dalleiger, Jilles Vreeken, Michael Kamp |
| 2024 | AISTATS | Orthogonal Gradient Boosting for Simpler Additive Rule Ensembles. | Fan Yang, Pierre Le Bodic, Michael Kamp, Mario Boley |
| 2024 | ICLR | Layer-wise linear mode connectivity. | Linara Adilova, Maksym Andriushchenko, Michael Kamp, Asja Fischer, Martin Jaggi |
| 2023 | AAAI | Information-Theoretic Causal Discovery and Intervention Detection over Multiple Environments. | Osman Mian, Michael Kamp, Jilles Vreeken |
| 2023 | AISTATS | Nothing but Regrets - Privacy-Preserving Federated Causal Discovery. | Osman Mian, David Kaltenpoth, Michael Kamp, Jilles Vreeken |
| 2023 | ICLR | Federated Learning from Small Datasets. | Michael Kamp, Jonas Fischer, Jilles Vreeken |
| 2021 | DSN | Third International Workshop on Data-Centric Dependability and Security (DCDS). | Ibria Medeiros, Ilir Gashi, Michael Kamp, Pedro Ferreira |
| 2021 | ICLR | FedBN: Federated Learning on Non-IID Features via Local Batch Normalization. | Xiaoxiao Li, Meirui Jiang, Xiaofei Zhang, Michael Kamp, Qi Dou |
| 2020 | DSN | Second International Workshop on Data-Centric Dependability and Security (DCDS). | Ibria Medeiros, Ilir Gashi, Michael Kamp, Pedro Ferreira |
| 2020 | KDD | HOPS: Probabilistic Subtree Mining for Small and Large Graphs. | Pascal Welke, Florian Seiffarth, Michael Kamp, Stefan Wrobel |
| 2019 | DSN | System Misuse Detection Via Informed Behavior Clustering and Modeling. | Linara Adilova, Livin Natious, Siming Chen, Olivier Thonnard, Michael Kamp |
| 2016 | ICDM | Ligand-Based Virtual Screening with Co-regularised Support Vector Regression. | Katrin Ullrich, Michael Kamp, Thomas Grtner, Martin Vogt, Stefan Wrobel |
| 2014 | SDM | Beating Human Analysts in Nowcasting Corporate Earnings by using Publicly Available Stock Price and Correlation Features. | Michael Kamp, Mario Boley, Thomas Grtner |
| 2013 | ICDM | Beating Human Analysts in Nowcasting Corporate Earnings by Using Publicly Available Stock Price and Correlation Features. | Michael Kamp, Mario Boley, Thomas Grtner |
| 2013 | VLDB | Communication-Efficient Distributed Online Prediction using Dynamic Model Synchronizations. | Mario Boley, Michael Kamp, Daniel Keren, Assaf Schuster, Izchak Sharfman |