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141 Publications
2026 |
Accepted |
Conference Paper |
IST-REx-ID: 21916
Damie, Marc, and Edwige Audrey Lucienne Cyffers. “Fedivertex: A Graph Dataset Based on Decentralized Social Media.” In 2026 Proceedings of the ACM Web Conference, 8393–96. ACM, n.d. https://doi.org/10.1145/3774904.3792868.
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| DOI
2026 |
Published |
Conference Paper |
IST-REx-ID: 22146 |
Kalinin, Nikita, and Joel D Andersson. “Learning Rate Scheduling with Matrix Factorization for Private Training.” In 7th Symposium on Foundations of Responsible Computing, Vol. 368. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2026. https://doi.org/10.4230/LIPIcs.FORC.2026.2.
[Published Version]
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| DOI
| arXiv
2026 |
Published |
Thesis | PhD |
IST-REx-ID: 21198 |
Scott, Jonathan A. “Data Heterogeneity and Personalization in Federated Learning.” Institute of Science and Technology Austria, 2026. https://doi.org/10.15479/AT-ISTA-21198.
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2025 |
Published |
Conference Paper |
IST-REx-ID: 20256 |
Henzinger, Thomas A, Fabian Kresse, Kaushik Mallik, Emily Yu, and Dorde Zikelic. “Predictive Monitoring of Black-Box Dynamical Systems.” In 7th Annual Learning for Dynamics & Control Conference, 283:804–16. ML Research Press, 2025.
[Published Version]
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| Files available
| arXiv
2025 |
Published |
Conference Paper |
IST-REx-ID: 20298 |
Kalinin, Nikita, and Lukas Steinberger. “Efficient Estimation of a Gaussian Mean with Local Differential Privacy.” In Proceedings of the 28th International Conference on Artificial Intelligence and Statistics, 258:118–26. ML Research Press, 2025.
[Published Version]
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| Files available
| arXiv
2025 |
Published |
Conference Paper |
IST-REx-ID: 22825 |
Súkeník, Peter, Christoph Lampert, and Marco Mondelli. “Neural Collapse Is Globally Optimal in Deep Regularized ResNets and Transformers.” In 39th Conference on Neural Information Processing Systems, 38:48646–77. Neural Information Processing Systems Foundation, 2025. https://doi.org/10.52202/085713-1450.
[Published Version]
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| arXiv
2025 |
Published |
Conference Paper |
IST-REx-ID: 22824 |
Zakerinia, Hossein, and Christoph Lampert. “Fast Rate Bounds for Multi-Task and Meta-Learning with Different Sample Sizes.” In 39th Conference on Neural Information Processing Systems, 38:9062–93. Neural Information Processing Systems Foundation, 2025. https://doi.org/10.52202/085713-0278.
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2025 |
Published |
Conference Paper |
IST-REx-ID: 20296 |
Kresse, Fabian, Emily Yu, Christoph Lampert, and Thomas A Henzinger. “Logic Gate Neural Networks Are Good for Verification.” In 2nd International Conferenceon Neuro-Symbolic Systems, Vol. 288. ML Research Press, 2025.
[Published Version]
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| arXiv
2025 |
Published |
Conference Paper |
IST-REx-ID: 20819 |
Scott, Jonathan A, Christoph Lampert, and David Saulpic. “Differentially Private Federated K-Means Clustering with Server-Side Data.” In 42nd International Conference on Machine Learning, 267:53757–90. ML Research Press, 2025.
[Published Version]
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| arXiv
2025 |
Draft |
Preprint |
IST-REx-ID: 21207 |
Zakerinia, Hossein, Jonathan A Scott, and Christoph Lampert. “Federated Learning with Unlabeled Clients: Personalization Can Happen in Low Dimensions.” ArXiv, n.d. https://doi.org/10.48550/ARXIV.2505.15579.
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2025 |
Published |
Conference Paper |
IST-REx-ID: 22828 |
Kalinin, Nikita, Jalaj Upadhyay, and Christoph Lampert. “Continual Release Moment Estimation with Differential Privacy.” In Advances in Neural Information Processing Systems, 38:64002–47. Neural Information Processing Systems Foundation, 2025. https://doi.org/10.52202/085713-1924.
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2025 |
Published |
Journal Article |
IST-REx-ID: 12662 |
| 
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Súkeník, Peter, and Christoph Lampert. “Generalization in Multi-Objective Machine Learning.” Neural Computing and Applications. Springer Nature, 2025. https://doi.org/10.1007/s00521-024-10616-1.
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| DOI
| arXiv
2025 |
Published |
Thesis | PhD |
IST-REx-ID: 19759 |
Prach, Bernd. “Robust Image Classification with 1-Lipschitz Networks.” Institute of Science and Technology Austria, 2025. https://doi.org/10.15479/10.15479/at-ista-19759.
[Published Version]
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| DOI
2025 |
Published |
Conference Paper |
IST-REx-ID: 20455 |
Prach, Bernd, and Christoph Lampert. “Intriguing Properties of Robust Classification.” In 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 660–69. IEEE, 2025. https://doi.org/10.1109/CVPRW67362.2025.00071.
[Preprint]
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| arXiv
2025 |
Published |
Conference Paper |
IST-REx-ID: 22823 |
Cyffers, Edwige Audrey Lucienne. “Setting ε Is Not the Issue in Differential Privacy.” In 39th Conference on Neural Information Processing Systems, 38:159016–28. Neural Information Processing Systems Foundation, 2025. https://doi.org/10.52202/085713-4798.
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2024 |
Published |
Journal Article |
IST-REx-ID: 19408 |
Verwimp, Eli, Rahaf Aljundi, Shai Ben-David, Matthias Bethge, Andrea Cossu, Alexander Gepperth, Tyler L. Hayes, et al. “Continual Learning: Applications and the Road Forward.” Transactions on Machine Learning Research. Transactions on Machine Learning Research, 2024.
[Published Version]
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| arXiv
2024 |
Submitted |
Preprint |
IST-REx-ID: 19063 |
Zverev, Egor, Sahar Abdelnabi, Soroush Tabesh, Mario Fritz, and Christoph Lampert. “Can LLMs Separate Instructions from Data? And What Do We Even Mean by That?” ArXiv, n.d. https://doi.org/10.48550/arXiv.2403.06833.
[Preprint]
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| DOI
| arXiv
2024 |
Published |
Conference Paper |
IST-REx-ID: 17411 |
Scott, Jonathan A, Hossein Zakerinia, and Christoph Lampert. “PEFLL: Personalized Federated Learning by Learning to Learn.” In 12th International Conference on Learning Representations. OpenReview, 2024.
[Published Version]
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| Files available
| arXiv
2024 |
Published |
Conference Paper |
IST-REx-ID: 18120 |
Scott, Jonathan A, and Áine Cahill. “Improved Modelling of Federated Datasets Using Mixtures-of-Dirichlet-Multinomials.” In Proceedings of the 41st International Conference on Machine Learning, 235:44012–37. ML Research Press, 2024.
[Preprint]
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| arXiv
2024 |
Published |
Conference Paper |
IST-REx-ID: 18118 |
Zakerinia, Hossein, Amin Behjati, and Christoph Lampert. “More Flexible PAC-Bayesian Meta-Learning by Learning Learning Algorithms.” In Proceedings of the 41st International Conference on Machine Learning, 235:58122–39. ML Research Press, 2024.
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| arXiv