Eugenia Iofinova

11 Publications

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[11]
2026 | Published | Journal Article | IST-REx-ID: 21839 | OA
Sin C, Watzenboeck ML, Iofinova EB, et al. Radiomics‐based assessment of portal hypertension severity and risk stratification of cirrhotic patients using routine CT scans. Liver International. 2026;46(5). doi:10.1111/liv.70633
[Published Version] View | Files available | DOI | PubMed | Europe PMC
 
[10]
2026 | Published | Thesis | PhD | IST-REx-ID: 21854 | OA
Iofinova EB. On the utility and effects of efficiency in artificial neural networks. 2026. doi:10.15479/AT-ISTA-21854
[Published Version] View | Files available | DOI
 
[9]
2026 | Published | Conference Poster | IST-REx-ID: 21857 | OA
Nicolicioiu A, Iofinova EB, Jovanovic A, et al. Panza: Investigating the Feasibility of Fully-Local Personalized Text Generation. OpenReview; 2026.
[Accepted Version] View | Files available | Download Accepted Version (ext.)
 
[8]
2026 | Draft | Preprint | IST-REx-ID: 21859 | OA
Iofinova EB, Alistarh D-A. Behemoth: Benchmarking unlearning in LLMs using fully synthetic data. arXiv. doi:10.48550/arXiv.2601.23153
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
[7]
2025 | Draft | Preprint | IST-REx-ID: 21858 | OA
Iofinova EB, Jovanovic A, Alistarh D-A. Position: It’s time to act on the risk of efficient personalized text generation. arXiv. doi:10.48550/arXiv.2502.06560
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
[6]
2024 | Published | Conference Paper | IST-REx-ID: 18121 | OA
Moakhar AS, Iofinova EB, Frantar E, Alistarh D-A. SPADE: Sparsity-guided debugging for deep neural networks. In: Proceedings of the 41st International Conference on Machine Learning. Vol 235. ML Research Press; 2024:45955-45987.
[Preprint] View | Files available | Download Preprint (ext.) | arXiv
 
[5]
2023 | Published | Conference Paper | IST-REx-ID: 14460 | OA
Nikdan M, Pegolotti T, Iofinova EB, Kurtic E, Alistarh D-A. SparseProp: Efficient sparse backpropagation for faster training of neural networks at the edge. In: Proceedings of the 40th International Conference on Machine Learning. Vol 202. ML Research Press; 2023:26215-26227.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[4]
2023 | Published | Conference Paper | IST-REx-ID: 14771 | OA
Iofinova EB, Krumes A, Alistarh D-A. Bias in pruned vision models: In-depth analysis and countermeasures. In: 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition. IEEE; 2023:24364-24373. doi:10.1109/cvpr52729.2023.02334
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS | arXiv
 
[3]
2022 | Published | Conference Paper | IST-REx-ID: 12299 | OA
Iofinova EB, Krumes A, Kurtz M, Alistarh D-A. How well do sparse ImageNet models transfer? In: 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition. Institute of Electrical and Electronics Engineers; 2022:12256-12266. doi:10.1109/cvpr52688.2022.01195
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS | arXiv
 
[2]
2022 | Published | Journal Article | IST-REx-ID: 12495 | OA
Iofinova EB, Konstantinov NH, Lampert C. FLEA: Provably robust fair multisource learning from unreliable training data. Transactions on Machine Learning Research. 2022.
[Published Version] View | Files available | Download Published Version (ext.) | arXiv
 
[1]
2021 | Published | Conference Paper | IST-REx-ID: 11458 | OA
Krumes A, Iofinova EB, Vladu A, Alistarh D-A. AC/DC: Alternating Compressed/DeCompressed training of deep neural networks. In: 35th Conference on Neural Information Processing Systems. Vol 34. Neural Information Processing Systems Foundation; 2021:8557-8570.
[Published Version] View | Files available | Download Published Version (ext.) | arXiv
 
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11 Publications

Mark all

[11]
2026 | Published | Journal Article | IST-REx-ID: 21839 | OA
Sin C, Watzenboeck ML, Iofinova EB, et al. Radiomics‐based assessment of portal hypertension severity and risk stratification of cirrhotic patients using routine CT scans. Liver International. 2026;46(5). doi:10.1111/liv.70633
[Published Version] View | Files available | DOI | PubMed | Europe PMC
 
[10]
2026 | Published | Thesis | PhD | IST-REx-ID: 21854 | OA
Iofinova EB. On the utility and effects of efficiency in artificial neural networks. 2026. doi:10.15479/AT-ISTA-21854
[Published Version] View | Files available | DOI
 
[9]
2026 | Published | Conference Poster | IST-REx-ID: 21857 | OA
Nicolicioiu A, Iofinova EB, Jovanovic A, et al. Panza: Investigating the Feasibility of Fully-Local Personalized Text Generation. OpenReview; 2026.
[Accepted Version] View | Files available | Download Accepted Version (ext.)
 
[8]
2026 | Draft | Preprint | IST-REx-ID: 21859 | OA
Iofinova EB, Alistarh D-A. Behemoth: Benchmarking unlearning in LLMs using fully synthetic data. arXiv. doi:10.48550/arXiv.2601.23153
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
[7]
2025 | Draft | Preprint | IST-REx-ID: 21858 | OA
Iofinova EB, Jovanovic A, Alistarh D-A. Position: It’s time to act on the risk of efficient personalized text generation. arXiv. doi:10.48550/arXiv.2502.06560
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
[6]
2024 | Published | Conference Paper | IST-REx-ID: 18121 | OA
Moakhar AS, Iofinova EB, Frantar E, Alistarh D-A. SPADE: Sparsity-guided debugging for deep neural networks. In: Proceedings of the 41st International Conference on Machine Learning. Vol 235. ML Research Press; 2024:45955-45987.
[Preprint] View | Files available | Download Preprint (ext.) | arXiv
 
[5]
2023 | Published | Conference Paper | IST-REx-ID: 14460 | OA
Nikdan M, Pegolotti T, Iofinova EB, Kurtic E, Alistarh D-A. SparseProp: Efficient sparse backpropagation for faster training of neural networks at the edge. In: Proceedings of the 40th International Conference on Machine Learning. Vol 202. ML Research Press; 2023:26215-26227.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[4]
2023 | Published | Conference Paper | IST-REx-ID: 14771 | OA
Iofinova EB, Krumes A, Alistarh D-A. Bias in pruned vision models: In-depth analysis and countermeasures. In: 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition. IEEE; 2023:24364-24373. doi:10.1109/cvpr52729.2023.02334
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS | arXiv
 
[3]
2022 | Published | Conference Paper | IST-REx-ID: 12299 | OA
Iofinova EB, Krumes A, Kurtz M, Alistarh D-A. How well do sparse ImageNet models transfer? In: 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition. Institute of Electrical and Electronics Engineers; 2022:12256-12266. doi:10.1109/cvpr52688.2022.01195
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS | arXiv
 
[2]
2022 | Published | Journal Article | IST-REx-ID: 12495 | OA
Iofinova EB, Konstantinov NH, Lampert C. FLEA: Provably robust fair multisource learning from unreliable training data. Transactions on Machine Learning Research. 2022.
[Published Version] View | Files available | Download Published Version (ext.) | arXiv
 
[1]
2021 | Published | Conference Paper | IST-REx-ID: 11458 | OA
Krumes A, Iofinova EB, Vladu A, Alistarh D-A. AC/DC: Alternating Compressed/DeCompressed training of deep neural networks. In: 35th Conference on Neural Information Processing Systems. Vol 34. Neural Information Processing Systems Foundation; 2021:8557-8570.
[Published Version] View | Files available | Download Published Version (ext.) | arXiv
 
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Citation Style: AMA

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