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141 Publications
2026 |
Published |
Conference Paper |
IST-REx-ID: 22146 |
N. Kalinin and J. D. Andersson, “Learning rate scheduling with matrix factorization for private training,” in 7th Symposium on Foundations of Responsible Computing, Cambridge, MA; United States, 2026, vol. 368.
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| arXiv
2026 |
Published |
Thesis | PhD |
IST-REx-ID: 21198 |
J. A. Scott, “Data heterogeneity and personalization in federated learning,” Institute of Science and Technology Austria, 2026.
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2025 |
Published |
Conference Paper |
IST-REx-ID: 20256 |
T. A. Henzinger, F. Kresse, K. Mallik, E. Yu, and D. Zikelic, “Predictive monitoring of black-box dynamical systems,” in 7th Annual Learning for Dynamics & Control Conference, Ann Arbor, MI, United States, 2025, vol. 283, pp. 804–816.
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| arXiv
2025 |
Published |
Conference Paper |
IST-REx-ID: 20298 |
N. Kalinin and L. Steinberger, “Efficient estimation of a Gaussian mean with local differential privacy,” in Proceedings of the 28th International Conference on Artificial Intelligence and Statistics, Mai Khao, Thailand, 2025, vol. 258, pp. 118–126.
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| arXiv
2025 |
Published |
Conference Paper |
IST-REx-ID: 22825 |
P. Súkeník, C. Lampert, and M. Mondelli, “Neural collapse is globally optimal in deep regularized ResNets and transformers,” in 39th Conference on Neural Information Processing Systems, San Diego, CA, United States, 2025, vol. 38, pp. 48646–48677.
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| arXiv
2025 |
Published |
Conference Paper |
IST-REx-ID: 22824 |
H. Zakerinia and C. Lampert, “Fast rate bounds for multi-task and meta-learning with different sample sizes,” in 39th Conference on Neural Information Processing Systems, San Diego, CA, United States, 2025, vol. 38, pp. 9062–9093.
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2025 |
Published |
Conference Paper |
IST-REx-ID: 20296 |
F. Kresse, E. Yu, C. Lampert, and T. A. Henzinger, “Logic gate neural networks are good for verification,” in 2nd International Conferenceon Neuro-Symbolic Systems, Philadephia, PA, United States, 2025, vol. 288.
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| arXiv
2025 |
Published |
Conference Paper |
IST-REx-ID: 20819 |
J. A. Scott, C. Lampert, and D. Saulpic, “Differentially private federated k-means clustering with server-side data,” in 42nd International Conference on Machine Learning, Vancouver, Canada, 2025, vol. 267, pp. 53757–53790.
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| arXiv
2025 |
Draft |
Preprint |
IST-REx-ID: 21207 |
H. Zakerinia, J. A. Scott, and C. Lampert, “Federated learning with unlabeled clients: Personalization can happen in low dimensions,” arXiv. .
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2025 |
Published |
Conference Paper |
IST-REx-ID: 22823 |
E. A. L. Cyffers, “Setting ε is not the issue in differential privacy,” in 39th Conference on Neural Information Processing Systems, San Diego, CA, United States, 2025, vol. 38, pp. 159016–159028.
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2025 |
Published |
Conference Paper |
IST-REx-ID: 22828 |
N. Kalinin, J. Upadhyay, and C. Lampert, “Continual release moment estimation with differential privacy,” in Advances in Neural Information Processing Systems, San Diego, CA, United States, 2025, vol. 38, pp. 64002–64047.
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2025 |
Published |
Journal Article |
IST-REx-ID: 12662 |
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P. Súkeník and C. Lampert, “Generalization in multi-objective machine learning,” Neural Computing and Applications, vol. 37. Springer Nature, pp. 24669–24683, 2025.
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| arXiv
2025 |
Published |
Thesis | PhD |
IST-REx-ID: 19759 |
B. Prach, “Robust image classification with 1-Lipschitz networks,” Institute of Science and Technology Austria, 2025.
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2025 |
Published |
Conference Paper |
IST-REx-ID: 20455 |
B. Prach and C. Lampert, “Intriguing properties of robust classification,” in 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, Nashville, TN, United States, 2025, pp. 660–669.
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| arXiv
2024 |
Published |
Journal Article |
IST-REx-ID: 18856 |
K. Lutsai and C. Lampert, “Predicting the geolocation of tweets using transformer models on customized data,” Journal of Spatial Information Science, no. 29. University of Maine, pp. 69–99, 2024.
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2024 |
Published |
Journal Article |
IST-REx-ID: 19408 |
E. Verwimp et al., “Continual learning: Applications and the road forward,” Transactions on Machine Learning Research, vol. 2024. Transactions on Machine Learning Research, 2024.
[Published Version]
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| arXiv
2024 |
Submitted |
Preprint |
IST-REx-ID: 19063 |
E. Zverev, S. Abdelnabi, S. Tabesh, M. Fritz, and C. Lampert, “Can LLMs separate instructions from data? And what do we even mean by that?,” arXiv. .
[Preprint]
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| DOI
| arXiv
2024 |
Published |
Conference Paper |
IST-REx-ID: 17411 |
J. A. Scott, H. Zakerinia, and C. Lampert, “PEFLL: Personalized federated learning by learning to learn,” in 12th International Conference on Learning Representations, Vienna, Austria, 2024.
[Published Version]
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| arXiv
2024 |
Published |
Conference Paper |
IST-REx-ID: 18120 |
J. A. Scott and Á. Cahill, “Improved modelling of federated datasets using mixtures-of-Dirichlet-multinomials,” in Proceedings of the 41st International Conference on Machine Learning, Vienna, Austria, 2024, vol. 235, pp. 44012–44037.
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| arXiv