Elias Frantar
Graduate School
Alistarh Group
3 Publications
2023 | Conference Paper | IST-REx-ID: 14458 | 
E. Frantar and D.-A. Alistarh, “SparseGPT: Massive language models can be accurately pruned in one-shot,” in Proceedings of the 40th International Conference on Machine Learning, Honolulu, Hawaii, HI, United States, 2023, vol. 202, pp. 10323–10337.
[Preprint]
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| arXiv
2021 | Conference Paper | IST-REx-ID: 11463 |
E. Frantar, E. Kurtic, and D.-A. Alistarh, “M-FAC: Efficient matrix-free approximations of second-order information,” in 35th Conference on Neural Information Processing Systems, Virtual, Online, 2021, vol. 34, pp. 14873–14886.
[Published Version]
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| arXiv
2020 | Conference Paper | IST-REx-ID: 8724 |
N. H. Konstantinov, E. Frantar, D.-A. Alistarh, and C. Lampert, “On the sample complexity of adversarial multi-source PAC learning,” in Proceedings of the 37th International Conference on Machine Learning, Online, 2020, vol. 119, pp. 5416–5425.
[Published Version]
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| Files available
| arXiv
3 Publications
2023 | Conference Paper | IST-REx-ID: 14458 |
E. Frantar and D.-A. Alistarh, “SparseGPT: Massive language models can be accurately pruned in one-shot,” in Proceedings of the 40th International Conference on Machine Learning, Honolulu, Hawaii, HI, United States, 2023, vol. 202, pp. 10323–10337.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
2021 | Conference Paper | IST-REx-ID: 11463 |
E. Frantar, E. Kurtic, and D.-A. Alistarh, “M-FAC: Efficient matrix-free approximations of second-order information,” in 35th Conference on Neural Information Processing Systems, Virtual, Online, 2021, vol. 34, pp. 14873–14886.
[Published Version]
View
| Download Published Version (ext.)
| arXiv
2020 | Conference Paper | IST-REx-ID: 8724 |
N. H. Konstantinov, E. Frantar, D.-A. Alistarh, and C. Lampert, “On the sample complexity of adversarial multi-source PAC learning,” in Proceedings of the 37th International Conference on Machine Learning, Online, 2020, vol. 119, pp. 5416–5425.
[Published Version]
View
| Files available
| arXiv