Eugenia Iofinova
Graduate School
Alistarh Group
5 Publications
2023 | Published | Conference Paper | IST-REx-ID: 14460 | 
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.
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2023 | Published | Conference Paper | IST-REx-ID: 14771 |
E. B. Iofinova, E.-A. Peste, and D.-A. Alistarh, “Bias in pruned vision models: In-depth analysis and countermeasures,” in 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition, Vancouver, BC, Canada, 2023, pp. 24364–24373.
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2022 | Published | Conference Paper | IST-REx-ID: 12299 |
E. B. Iofinova, E.-A. Peste, M. Kurtz, and D.-A. Alistarh, “How well do sparse ImageNet models transfer?,” in 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition, New Orleans, LA, United States, 2022, pp. 12256–12266.
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2022 | Published | Journal Article | IST-REx-ID: 12495 |
E. B. Iofinova, N. H. Konstantinov, and C. Lampert, “FLEA: Provably robust fair multisource learning from unreliable training data,” Transactions on Machine Learning Research. ML Research Press, 2022.
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2021 | Published | Conference Paper | IST-REx-ID: 11458 |
E.-A. Peste, E. B. Iofinova, A. Vladu, and D.-A. Alistarh, “AC/DC: Alternating Compressed/DeCompressed training of deep neural networks,” in 35th Conference on Neural Information Processing Systems, Virtual, Online, 2021, vol. 34, pp. 8557–8570.
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Grants
5 Publications
2023 | Published | Conference Paper | IST-REx-ID: 14460 |
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
2023 | Published | Conference Paper | IST-REx-ID: 14771 |
E. B. Iofinova, E.-A. Peste, and D.-A. Alistarh, “Bias in pruned vision models: In-depth analysis and countermeasures,” in 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition, Vancouver, BC, Canada, 2023, pp. 24364–24373.
[Preprint]
View
| Files available
| DOI
| Download Preprint (ext.)
| WoS
| arXiv
2022 | Published | Conference Paper | IST-REx-ID: 12299 |
E. B. Iofinova, E.-A. Peste, M. Kurtz, and D.-A. Alistarh, “How well do sparse ImageNet models transfer?,” in 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition, New Orleans, LA, United States, 2022, pp. 12256–12266.
[Preprint]
View
| Files available
| DOI
| Download Preprint (ext.)
| WoS
| arXiv
2022 | Published | Journal Article | IST-REx-ID: 12495 |
E. B. Iofinova, N. H. Konstantinov, and C. Lampert, “FLEA: Provably robust fair multisource learning from unreliable training data,” Transactions on Machine Learning Research. ML Research Press, 2022.
[Published Version]
View
| Files available
| Download Published Version (ext.)
| arXiv
2021 | Published | Conference Paper | IST-REx-ID: 11458 |
E.-A. Peste, E. B. Iofinova, A. Vladu, and D.-A. Alistarh, “AC/DC: Alternating Compressed/DeCompressed training of deep neural networks,” in 35th Conference on Neural Information Processing Systems, Virtual, Online, 2021, vol. 34, pp. 8557–8570.
[Published Version]
View
| Files available
| Download Published Version (ext.)
| arXiv