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135 Publications
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, doi:10.15479/AT-ISTA-21198.
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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, vol. 37, Springer Nature, 2025, pp. 24669–24683, doi:10.1007/s00521-024-10616-1.
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| arXiv
2025 |
Published |
Conference Paper |
IST-REx-ID: 20256 |
Henzinger, Thomas A., et al. “Predictive Monitoring of Black-Box Dynamical Systems.” 7th Annual Learning for Dynamics & Control Conference, vol. 283, ML Research Press, 2025, pp. 804–16.
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| arXiv
2025 |
Published |
Conference Paper |
IST-REx-ID: 20296 |
Kresse, Fabian, et al. “Logic Gate Neural Networks Are Good for Verification.” 2nd International Conferenceon Neuro-Symbolic Systems, vol. 288, 26, ML Research Press, 2025.
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| arXiv
2025 |
Published |
Conference Paper |
IST-REx-ID: 20298 |
Kalinin, Nikita, and Lukas Steinberger. “Efficient Estimation of a Gaussian Mean with Local Differential Privacy.” Proceedings of the 28th International Conference on Artificial Intelligence and Statistics, vol. 258, ML Research Press, 2025, pp. 118–26.
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| arXiv
2025 |
Published |
Conference Paper |
IST-REx-ID: 20455 |
Prach, Bernd, and Christoph Lampert. “Intriguing Properties of Robust Classification.” 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, IEEE, 2025, pp. 660–69, doi:10.1109/CVPRW67362.2025.00071.
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| arXiv
2025 |
Published |
Conference Paper |
IST-REx-ID: 20819 |
Scott, Jonathan A., et al. “Differentially Private Federated K-Means Clustering with Server-Side Data.” 42nd International Conference on Machine Learning, vol. 267, ML Research Press, 2025, pp. 53757–90.
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| 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, doi:10.15479/10.15479/at-ista-19759.
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2025 |
Draft |
Preprint |
IST-REx-ID: 21207 |
Zakerinia, Hossein, et al. “Federated Learning with Unlabeled Clients: Personalization Can Happen in Low Dimensions.” ArXiv, doi:10.48550/ARXIV.2505.15579.
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2024 |
Published |
Conference Paper |
IST-REx-ID: 18118 |
Zakerinia, Hossein, et al. “More Flexible PAC-Bayesian Meta-Learning by Learning Learning Algorithms.” Proceedings of the 41st International Conference on Machine Learning, vol. 235, ML Research Press, 2024, pp. 58122–39.
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| 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.” Proceedings of the 41st International Conference on Machine Learning, vol. 235, ML Research Press, 2024, pp. 44012–37.
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| arXiv
2024 |
Published |
Journal Article |
IST-REx-ID: 18856 |
Lutsai, Kateryna, and Christoph Lampert. “Predicting the Geolocation of Tweets Using Transformer Models on Customized Data.” Journal of Spatial Information Science, no. 29, University of Maine, 2024, pp. 69–99, doi:10.5311/JOSIS.2024.29.295.
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2024 |
Draft |
Preprint |
IST-REx-ID: 18874 |
Prach, Bernd, and Christoph Lampert. “Intriguing Properties of Robust Classification.” ArXiv, 2412.04245, doi:10.48550/arXiv.2412.04245.
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| arXiv
2024 |
Published |
Conference Paper |
IST-REx-ID: 18875 |
Kalinin, Nikita, and Christoph Lampert. “Banded Square Root Matrix Factorization for Differentially Private Model Training.” 38th Annual Conference on Neural Information Processing Systems, vol. 37, Neural Information Processing Systems Foundation, 2024.
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| arXiv
2024 |
Published |
Conference Paper |
IST-REx-ID: 18891 |
Súkeník, Peter, et al. “Neural Collapse versus Low-Rank Bias: Is Deep Neural Collapse Really Optimal?” 38th Annual Conference on Neural Information Processing Systems, vol. 37, Neural Information Processing Systems Foundation, 2024.
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| arXiv
2024 |
Published |
Preprint |
IST-REx-ID: 19063 |
Zverev, Egor, et al. “Can LLMs Separate Instructions from Data? And What Do We Even Mean by That?” ArXiv, 2403.06833, 2024, doi:10.48550/arXiv.2403.06833.
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| arXiv
2024 |
Published |
Journal Article |
IST-REx-ID: 19408 |
Verwimp, Eli, et al. “Continual Learning: Applications and the Road Forward.” Transactions on Machine Learning Research, vol. 2024, Transactions on Machine Learning Research, 2024.
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| arXiv
2024 |
Published |
Conference Paper |
IST-REx-ID: 17093 |
Zakerinia, Hossein, et al. “Communication-Efficient Federated Learning with Data and Client Heterogeneity.” Proceedings of the 27th International Conference on Artificial Intelligence and Statistics, vol. 238, ML Research Press, 2024, pp. 3448–56.
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| arXiv
2024 |
Published |
Conference Paper |
IST-REx-ID: 17411 |
Scott, Jonathan A., et al. “PEFLL: Personalized Federated Learning by Learning to Learn.” 12th International Conference on Learning Representations, OpenReview, 2024.
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| arXiv
2024 |
Published |
Conference Paper |
IST-REx-ID: 17426 |
Prach, Bernd, et al. “1-Lipschitz Layers Compared: Memory, Speed, and Certifiable Robustness.” Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, Computer Vision Foundation, 2024, pp. 24574–83, doi:10.1109/CVPR52733.2024.02320.
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| arXiv