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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.” 2026 Proceedings of the ACM Web Conference, ACM, pp. 8393–96, doi:10.1145/3774904.3792868.
View | DOI
 
2026 | Published | Conference Paper | IST-REx-ID: 22146 | OA
Kalinin, Nikita, and Joel D. Andersson. “Learning Rate Scheduling with Matrix Factorization for Private Training.” 7th Symposium on Foundations of Responsible Computing, vol. 368, 2:1-2:21, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2026, doi:10.4230/LIPIcs.FORC.2026.2.
[Published Version] View | Files available | DOI | arXiv
 
2026 | Published | Thesis | PhD | IST-REx-ID: 21198 | OA
Scott, Jonathan A. Data Heterogeneity and Personalization in Federated Learning. Institute of Science and Technology Austria, 2026, doi:10.15479/AT-ISTA-21198.
[Published Version] View | Files available | DOI
 
2025 | Published | Conference Paper | IST-REx-ID: 20256 | OA
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.
[Published Version] View | Files available | arXiv
 
2025 | Published | Conference Paper | IST-REx-ID: 20298 | OA
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.
[Published Version] View | Files available | arXiv
 
2025 | Published | Conference Paper | IST-REx-ID: 22825 | OA
Súkeník, Peter, et al. “Neural Collapse Is Globally Optimal in Deep Regularized ResNets and Transformers.” 39th Conference on Neural Information Processing Systems, vol. 38, Neural Information Processing Systems Foundation, 2025, pp. 48646–77, doi:10.52202/085713-1450.
[Published Version] View | DOI | Download Published Version (ext.) | arXiv
 
2025 | Published | Conference Paper | IST-REx-ID: 22824 | OA
Zakerinia, Hossein, and Christoph Lampert. “Fast Rate Bounds for Multi-Task and Meta-Learning with Different Sample Sizes.” 39th Conference on Neural Information Processing Systems, vol. 38, Neural Information Processing Systems Foundation, 2025, pp. 9062–93, doi:10.52202/085713-0278.
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2025 | Published | Conference Paper | IST-REx-ID: 20296 | OA
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.
[Published Version] View | Files available | arXiv
 
2025 | Published | Conference Paper | IST-REx-ID: 20819 | OA
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.
[Published Version] View | Files available | arXiv
 
2025 | Draft | Preprint | IST-REx-ID: 21207 | OA
Zakerinia, Hossein, et al. “Federated Learning with Unlabeled Clients: Personalization Can Happen in Low Dimensions.” ArXiv, 2505.15579, doi:10.48550/ARXIV.2505.15579.
[Preprint] View | Files available | DOI | Download Preprint (ext.)
 
2025 | Published | Conference Paper | IST-REx-ID: 22823 | OA
Cyffers, Edwige Audrey Lucienne. “Setting ε Is Not the Issue in Differential Privacy.” 39th Conference on Neural Information Processing Systems, vol. 38, Neural Information Processing Systems Foundation, 2025, pp. 159016–28, doi:10.52202/085713-4798.
[Published Version] View | DOI | Download Published Version (ext.)
 
2025 | Published | Conference Paper | IST-REx-ID: 22828 | OA
Kalinin, Nikita, et al. “Continual Release Moment Estimation with Differential Privacy.” Advances in Neural Information Processing Systems, vol. 38, Neural Information Processing Systems Foundation, 2025, pp. 64002–47, doi:10.52202/085713-1924.
[Published Version] View | DOI | Download Published Version (ext.)
 
2025 | Published | Journal Article | IST-REx-ID: 12662 | OA | PlanS
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.
[Published Version] View | Files available | DOI | arXiv
 
2025 | Published | Thesis | PhD | IST-REx-ID: 19759 | OA
Prach, Bernd. Robust Image Classification with 1-Lipschitz Networks. Institute of Science and Technology Austria, 2025, doi:10.15479/10.15479/at-ista-19759.
[Published Version] View | Files available | DOI
 
2025 | Published | Conference Paper | IST-REx-ID: 20455 | OA
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.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
2024 | Published | Journal Article | IST-REx-ID: 18856 | OA
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.
[Published Version] View | Files available | DOI
 
2024 | Published | Journal Article | IST-REx-ID: 19408 | OA
Verwimp, Eli, et al. “Continual Learning: Applications and the Road Forward.” Transactions on Machine Learning Research, vol. 2024, Transactions on Machine Learning Research, 2024.
[Published Version] View | Files available | arXiv
 
2024 | Submitted | Preprint | IST-REx-ID: 19063 | OA
Zverev, Egor, et al. “Can LLMs Separate Instructions from Data? And What Do We Even Mean by That?” ArXiv, 2403.06833, doi:10.48550/arXiv.2403.06833.
[Preprint] View | Files available | DOI | arXiv
 
2024 | Published | Conference Paper | IST-REx-ID: 17411 | OA
Scott, Jonathan A., et al. “PEFLL: Personalized Federated Learning by Learning to Learn.” 12th International Conference on Learning Representations, OpenReview, 2024.
[Published Version] View | Files available | arXiv
 
2024 | Published | Conference Paper | IST-REx-ID: 18120 | OA
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.
[Preprint] View | Files available | Download Preprint (ext.) | arXiv
 

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