Elena-Alexandra Peste
Graduate School
Alistarh Group
Lampert Group
6 Publications
2023 | Conference Paper | IST-REx-ID: 13053 | 
Peste, Elena-Alexandra, et al. “CrAM: A Compression-Aware Minimizer.” 11th International Conference on Learning Representations .
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2023 | Thesis | IST-REx-ID: 13074 |
Peste, Elena-Alexandra. Efficiency and Generalization of Sparse Neural Networks. Institute of Science and Technology Austria, 2023, doi:10.15479/at:ista:13074.
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2023 | 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.
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2022 | 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.
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2021 | Journal Article | IST-REx-ID: 10180 |
Hoefler, Torsten, et al. “Sparsity in Deep Learning: Pruning and Growth for Efficient Inference and Training in Neural Networks.” Journal of Machine Learning Research, vol. 22, no. 241, Journal of Machine Learning Research, 2021, pp. 1–124.
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2021 | Conference Paper | IST-REx-ID: 11458 |
Peste, Elena-Alexandra, et al. “AC/DC: Alternating Compressed/DeCompressed Training of Deep Neural Networks.” 35th Conference on Neural Information Processing Systems, vol. 34, Curran Associates, 2021, pp. 8557–70.
[Published Version]
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6 Publications
2023 | Conference Paper | IST-REx-ID: 13053 |
Peste, Elena-Alexandra, et al. “CrAM: A Compression-Aware Minimizer.” 11th International Conference on Learning Representations .
[Preprint]
View
| Files available
| Download Preprint (ext.)
| arXiv
2023 | Thesis | IST-REx-ID: 13074 |
Peste, Elena-Alexandra. Efficiency and Generalization of Sparse Neural Networks. Institute of Science and Technology Austria, 2023, doi:10.15479/at:ista:13074.
[Published Version]
View
| Files available
| DOI
2023 | 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 | 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
2021 | Journal Article | IST-REx-ID: 10180 |
Hoefler, Torsten, et al. “Sparsity in Deep Learning: Pruning and Growth for Efficient Inference and Training in Neural Networks.” Journal of Machine Learning Research, vol. 22, no. 241, Journal of Machine Learning Research, 2021, pp. 1–124.
[Published Version]
View
| Files available
| Download Published Version (ext.)
| arXiv
2021 | Conference Paper | IST-REx-ID: 11458 |
Peste, Elena-Alexandra, et al. “AC/DC: Alternating Compressed/DeCompressed Training of Deep Neural Networks.” 35th Conference on Neural Information Processing Systems, vol. 34, Curran Associates, 2021, pp. 8557–70.
[Published Version]
View
| Files available
| Download Published Version (ext.)
| arXiv