Hossein Zakerinia

3 Publications

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[3]
2024 | Published | Conference Paper | IST-REx-ID: 17093 | OA
H. Zakerinia, S. Talaei, G. Nadiradze, and D.-A. Alistarh, “Communication-efficient federated learning with data and client heterogeneity,” in Proceedings of the 27th International Conference on Artificial Intelligence and Statistics, Valencia, Spain, 2024, vol. 238, pp. 3448–3456.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[2]
2024 | Published | Conference Paper | IST-REx-ID: 17411 | OA
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] View | Files available | arXiv
 
[1]
2024 | Published | Conference Paper | IST-REx-ID: 18118 | OA
H. Zakerinia, A. Behjati, and C. Lampert, “More flexible PAC-Bayesian meta-learning by learning learning algorithms,” in Proceedings of the 41st International Conference on Machine Learning, Vienna, Austria, 2024, vol. 235, pp. 58122–58139.
[Published Version] View | Download Published Version (ext.) | arXiv
 
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3 Publications

Mark all

[3]
2024 | Published | Conference Paper | IST-REx-ID: 17093 | OA
H. Zakerinia, S. Talaei, G. Nadiradze, and D.-A. Alistarh, “Communication-efficient federated learning with data and client heterogeneity,” in Proceedings of the 27th International Conference on Artificial Intelligence and Statistics, Valencia, Spain, 2024, vol. 238, pp. 3448–3456.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[2]
2024 | Published | Conference Paper | IST-REx-ID: 17411 | OA
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] View | Files available | arXiv
 
[1]
2024 | Published | Conference Paper | IST-REx-ID: 18118 | OA
H. Zakerinia, A. Behjati, and C. Lampert, “More flexible PAC-Bayesian meta-learning by learning learning algorithms,” in Proceedings of the 41st International Conference on Machine Learning, Vienna, Austria, 2024, vol. 235, pp. 58122–58139.
[Published Version] View | Download Published Version (ext.) | arXiv
 
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Citation Style: IEEE

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