Jonathan A Scott

6 Publications

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[6]
2026 | Published | Thesis | PhD | IST-REx-ID: 21198 | OA
Scott JA. 2026. Data heterogeneity and personalization in federated learning. Institute of Science and Technology Austria.
[Published Version] View | Files available | DOI
 
[5]
2025 | Published | Conference Paper | IST-REx-ID: 20819 | OA
Scott JA, Lampert C, Saulpic D. 2025. Differentially private federated k-means clustering with server-side data. 42nd International Conference on Machine Learning. ICML: International Conference on Machine Learning, PMLR, vol. 267, 53757–53790.
[Published Version] View | Files available | arXiv
 
[4]
2025 | Draft | Preprint | IST-REx-ID: 21207 | OA
Zakerinia H, Scott JA, Lampert C. Federated learning with unlabeled clients: Personalization can happen in low dimensions. arXiv, 10.48550/ARXIV.2505.15579.
[Preprint] View | Files available | DOI | Download Preprint (ext.)
 
[3]
2024 | Published | Conference Paper | IST-REx-ID: 18120 | OA
Scott JA, Cahill Á. 2024. Improved modelling of federated datasets using mixtures-of-Dirichlet-multinomials. Proceedings of the 41st International Conference on Machine Learning. ICML: International Conference on Machine Learning, PMLR, vol. 235, 44012–44037.
[Preprint] View | Files available | Download Preprint (ext.) | arXiv
 
[2]
2024 | Published | Conference Paper | IST-REx-ID: 17411 | OA
Scott JA, Zakerinia H, Lampert C. 2024. PEFLL: Personalized federated learning by learning to learn. 12th International Conference on Learning Representations. ICLR: International Conference on Learning Representations.
[Published Version] View | Files available | arXiv
 
[1]
2023 | Published | Conference Paper | IST-REx-ID: 12660 | OA
Scott JA, Yeo MX, Lampert C. 2023. Cross-client label propagation for transductive and semi-supervised federated learning. Transactions in Machine Learning. , TMLR, .
[Preprint] View | Files available | arXiv
 
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6 Publications

Mark all

[6]
2026 | Published | Thesis | PhD | IST-REx-ID: 21198 | OA
Scott JA. 2026. Data heterogeneity and personalization in federated learning. Institute of Science and Technology Austria.
[Published Version] View | Files available | DOI
 
[5]
2025 | Published | Conference Paper | IST-REx-ID: 20819 | OA
Scott JA, Lampert C, Saulpic D. 2025. Differentially private federated k-means clustering with server-side data. 42nd International Conference on Machine Learning. ICML: International Conference on Machine Learning, PMLR, vol. 267, 53757–53790.
[Published Version] View | Files available | arXiv
 
[4]
2025 | Draft | Preprint | IST-REx-ID: 21207 | OA
Zakerinia H, Scott JA, Lampert C. Federated learning with unlabeled clients: Personalization can happen in low dimensions. arXiv, 10.48550/ARXIV.2505.15579.
[Preprint] View | Files available | DOI | Download Preprint (ext.)
 
[3]
2024 | Published | Conference Paper | IST-REx-ID: 18120 | OA
Scott JA, Cahill Á. 2024. Improved modelling of federated datasets using mixtures-of-Dirichlet-multinomials. Proceedings of the 41st International Conference on Machine Learning. ICML: International Conference on Machine Learning, PMLR, vol. 235, 44012–44037.
[Preprint] View | Files available | Download Preprint (ext.) | arXiv
 
[2]
2024 | Published | Conference Paper | IST-REx-ID: 17411 | OA
Scott JA, Zakerinia H, Lampert C. 2024. PEFLL: Personalized federated learning by learning to learn. 12th International Conference on Learning Representations. ICLR: International Conference on Learning Representations.
[Published Version] View | Files available | arXiv
 
[1]
2023 | Published | Conference Paper | IST-REx-ID: 12660 | OA
Scott JA, Yeo MX, Lampert C. 2023. Cross-client label propagation for transductive and semi-supervised federated learning. Transactions in Machine Learning. , TMLR, .
[Preprint] View | Files available | arXiv
 
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Citation Style: ISTA Annual Report

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