Eugenia Iofinova
11 Publications
2026 |
Published |
Journal Article |
IST-REx-ID: 21839 |
Sin, Celine, et al. “Radiomics‐based Assessment of Portal Hypertension Severity and Risk Stratification of Cirrhotic Patients Using Routine CT Scans.” Liver International, vol. 46, no. 5, e70633, Wiley, 2026, doi:10.1111/liv.70633.
[Published Version]
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| DOI
| PubMed | Europe PMC
2026 |
Published |
Thesis | PhD |
IST-REx-ID: 21854 |
Iofinova, Eugenia B. On the Utility and Effects of Efficiency in Artificial Neural Networks. Institute of Science and Technology Austria, 2026, doi:10.15479/AT-ISTA-21854.
[Published Version]
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| Files available
| DOI
2026 |
Published |
Conference Poster |
IST-REx-ID: 21857 |
Nicolicioiu, Armand, et al. “Panza: Investigating the Feasibility of Fully-Local Personalized Text Generation.” Third Conference on Parsimony and Learning (Proceedings Track), 81, OpenReview, 2026.
[Accepted Version]
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2026 |
Draft |
Preprint |
IST-REx-ID: 21859 |
Iofinova, Eugenia B., and Dan-Adrian Alistarh. “Behemoth: Benchmarking Unlearning in LLMs Using Fully Synthetic Data.” ArXiv, doi:10.48550/arXiv.2601.23153.
[Preprint]
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| Files available
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| arXiv
2025 |
Draft |
Preprint |
IST-REx-ID: 21858 |
Iofinova, Eugenia B., et al. “Position: It’s Time to Act on the Risk of Efficient Personalized Text Generation.” ArXiv, doi:10.48550/arXiv.2502.06560.
[Preprint]
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| Files available
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| arXiv
2024 |
Published |
Conference Paper |
IST-REx-ID: 18121 |
Moakhar, Arshia Soltani, et al. “SPADE: Sparsity-Guided Debugging for Deep Neural Networks.” Proceedings of the 41st International Conference on Machine Learning, vol. 235, ML Research Press, 2024, pp. 45955–87.
[Preprint]
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| arXiv
2023 |
Published |
Conference Paper |
IST-REx-ID: 14460 |
Nikdan, Mahdi, et al. “SparseProp: Efficient Sparse Backpropagation for Faster Training of Neural Networks at the Edge.” Proceedings of the 40th International Conference on Machine Learning, vol. 202, ML Research Press, 2023, pp. 26215–27.
[Preprint]
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| Download Preprint (ext.)
| arXiv
2023 |
Published |
Conference Paper |
IST-REx-ID: 14771 |
Iofinova, Eugenia B., et al. “Bias in Pruned Vision Models: In-Depth Analysis and Countermeasures.” 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition, IEEE, 2023, pp. 24364–73, doi:10.1109/cvpr52729.2023.02334.
[Preprint]
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| Files available
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| WoS
| arXiv
2022 |
Published |
Conference Paper |
IST-REx-ID: 12299 |
Iofinova, Eugenia B., et al. “How Well Do Sparse ImageNet Models Transfer?” 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition, Institute of Electrical and Electronics Engineers, 2022, pp. 12256–66, doi:10.1109/cvpr52688.2022.01195.
[Preprint]
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| WoS
| arXiv
2022 |
Published |
Journal Article |
IST-REx-ID: 12495 |
Iofinova, Eugenia B., et al. “FLEA: Provably Robust Fair Multisource Learning from Unreliable Training Data.” Transactions on Machine Learning Research, ML Research Press, 2022.
[Published Version]
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| arXiv
2021 |
Published |
Conference Paper |
IST-REx-ID: 11458 |
Krumes, Alexandra, et al. “AC/DC: Alternating Compressed/DeCompressed Training of Deep Neural Networks.” 35th Conference on Neural Information Processing Systems, vol. 34, Neural Information Processing Systems Foundation, 2021, pp. 8557–70.
[Published Version]
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| Files available
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| arXiv
Grants
11 Publications
2026 |
Published |
Journal Article |
IST-REx-ID: 21839 |
Sin, Celine, et al. “Radiomics‐based Assessment of Portal Hypertension Severity and Risk Stratification of Cirrhotic Patients Using Routine CT Scans.” Liver International, vol. 46, no. 5, e70633, Wiley, 2026, doi:10.1111/liv.70633.
[Published Version]
View
| Files available
| DOI
| PubMed | Europe PMC
2026 |
Published |
Thesis | PhD |
IST-REx-ID: 21854 |
Iofinova, Eugenia B. On the Utility and Effects of Efficiency in Artificial Neural Networks. Institute of Science and Technology Austria, 2026, doi:10.15479/AT-ISTA-21854.
[Published Version]
View
| Files available
| DOI
2026 |
Published |
Conference Poster |
IST-REx-ID: 21857 |
Nicolicioiu, Armand, et al. “Panza: Investigating the Feasibility of Fully-Local Personalized Text Generation.” Third Conference on Parsimony and Learning (Proceedings Track), 81, OpenReview, 2026.
[Accepted Version]
View
| Files available
| Download Accepted Version (ext.)
2026 |
Draft |
Preprint |
IST-REx-ID: 21859 |
Iofinova, Eugenia B., and Dan-Adrian Alistarh. “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
2025 |
Draft |
Preprint |
IST-REx-ID: 21858 |
Iofinova, Eugenia B., et al. “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
2024 |
Published |
Conference Paper |
IST-REx-ID: 18121 |
Moakhar, Arshia Soltani, et al. “SPADE: Sparsity-Guided Debugging for Deep Neural Networks.” Proceedings of the 41st International Conference on Machine Learning, vol. 235, ML Research Press, 2024, pp. 45955–87.
[Preprint]
View
| Files available
| Download Preprint (ext.)
| arXiv
2023 |
Published |
Conference Paper |
IST-REx-ID: 14460 |
Nikdan, Mahdi, et al. “SparseProp: Efficient Sparse Backpropagation for Faster Training of Neural Networks at the Edge.” Proceedings of the 40th International Conference on Machine Learning, vol. 202, ML Research Press, 2023, pp. 26215–27.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
2023 |
Published |
Conference Paper |
IST-REx-ID: 14771 |
Iofinova, Eugenia B., et al. “Bias in Pruned Vision Models: In-Depth Analysis and Countermeasures.” 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition, IEEE, 2023, pp. 24364–73, doi:10.1109/cvpr52729.2023.02334.
[Preprint]
View
| Files available
| DOI
| Download Preprint (ext.)
| WoS
| arXiv
2022 |
Published |
Conference Paper |
IST-REx-ID: 12299 |
Iofinova, Eugenia B., et al. “How Well Do Sparse ImageNet Models Transfer?” 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition, Institute of Electrical and Electronics Engineers, 2022, pp. 12256–66, doi:10.1109/cvpr52688.2022.01195.
[Preprint]
View
| Files available
| DOI
| Download Preprint (ext.)
| WoS
| arXiv
2022 |
Published |
Journal Article |
IST-REx-ID: 12495 |
Iofinova, Eugenia B., et al. “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 |
Krumes, Alexandra, et al. “AC/DC: Alternating Compressed/DeCompressed Training of Deep Neural Networks.” 35th Conference on Neural Information Processing Systems, vol. 34, Neural Information Processing Systems Foundation, 2021, pp. 8557–70.
[Published Version]
View
| Files available
| Download Published Version (ext.)
| arXiv