Mahdi Nikdan

3 Publications

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[3]
2026 | Published | Conference Poster | IST-REx-ID: 21857 | OA
A. Nicolicioiu et al., Panza: Investigating the feasibility of fully-local personalized text generation. OpenReview, 2026.
[Accepted Version] View | Files available | Download Accepted Version (ext.)
 
[2]
2024 | Published | Conference Paper | IST-REx-ID: 18117 | OA
M. Nikdan, S. Tabesh, E. Crncevic, and D.-A. Alistarh, “RoSA: Accurate parameter-efficient fine-tuning via robust adaptation,” in Proceedings of the 41st International Conference on Machine Learning, Vienna, Austria, 2024, vol. 235, pp. 38187–38206.
[Preprint] View | Files available | Download Preprint (ext.) | arXiv
 
[1]
2023 | Published | Conference Paper | IST-REx-ID: 14460 | OA
M. Nikdan, T. Pegolotti, E. B. Iofinova, E. Kurtic, and D.-A. Alistarh, “SparseProp: Efficient sparse backpropagation for faster training of neural networks at the edge,” in Proceedings of the 40th International Conference on Machine Learning, Honolulu, Hawaii, HI, United States, 2023, vol. 202, pp. 26215–26227.
[Preprint] View | Download Preprint (ext.) | arXiv
 
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3 Publications

Mark all

[3]
2026 | Published | Conference Poster | IST-REx-ID: 21857 | OA
A. Nicolicioiu et al., Panza: Investigating the feasibility of fully-local personalized text generation. OpenReview, 2026.
[Accepted Version] View | Files available | Download Accepted Version (ext.)
 
[2]
2024 | Published | Conference Paper | IST-REx-ID: 18117 | OA
M. Nikdan, S. Tabesh, E. Crncevic, and D.-A. Alistarh, “RoSA: Accurate parameter-efficient fine-tuning via robust adaptation,” in Proceedings of the 41st International Conference on Machine Learning, Vienna, Austria, 2024, vol. 235, pp. 38187–38206.
[Preprint] View | Files available | Download Preprint (ext.) | arXiv
 
[1]
2023 | Published | Conference Paper | IST-REx-ID: 14460 | OA
M. Nikdan, T. Pegolotti, E. B. Iofinova, E. Kurtic, and D.-A. Alistarh, “SparseProp: Efficient sparse backpropagation for faster training of neural networks at the edge,” in Proceedings of the 40th International Conference on Machine Learning, Honolulu, Hawaii, HI, United States, 2023, vol. 202, pp. 26215–26227.
[Preprint] View | Download Preprint (ext.) | arXiv
 
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Citation Style: IEEE

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