Jonathan A Scott
6 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. https://doi.org/10.15479/AT-ISTA-21198.
[Published Version]
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| DOI
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]
View
| Files available
| 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.
[Preprint]
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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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| Files available
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| 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
2023 |
Published |
Conference Paper |
IST-REx-ID: 12660 |
Scott, Jonathan A, Michelle X Yeo, and Christoph Lampert. “Cross-Client Label Propagation for Transductive and Semi-Supervised Federated Learning.” In Transactions in Machine Learning. Curran Associates, 2023.
[Preprint]
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| Files available
| arXiv
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6 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. https://doi.org/10.15479/AT-ISTA-21198.
[Published Version]
View
| Files available
| DOI
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]
View
| Files available
| 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.
[Preprint]
View
| Files available
| DOI
| Download Preprint (ext.)
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]
View
| Files available
| Download Preprint (ext.)
| 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]
View
| Files available
| arXiv
2023 |
Published |
Conference Paper |
IST-REx-ID: 12660 |
Scott, Jonathan A, Michelle X Yeo, and Christoph Lampert. “Cross-Client Label Propagation for Transductive and Semi-Supervised Federated Learning.” In Transactions in Machine Learning. Curran Associates, 2023.
[Preprint]
View
| Files available
| arXiv