Peter Súkeník
3 Publications
2023 |
In Press |
Conference Paper |
IST-REx-ID: 14921 |
Súkeník P, Mondelli M, Lampert C. Deep neural collapse is provably optimal for the deep unconstrained features model. In: 37th Annual Conference on Neural Information Processing Systems.
[Preprint]
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| arXiv
2022 |
Submitted |
Preprint |
IST-REx-ID: 12662 |
Súkeník P, Lampert C. Generalization in Multi-objective machine learning. arXiv. doi:10.48550/arXiv.2208.13499
[Preprint]
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| DOI
| Download Preprint (ext.)
| arXiv
2022 |
Published |
Conference Paper |
IST-REx-ID: 12664 |
Súkeník P, Kuvshinov A, Günnemann S. Intriguing properties of input-dependent randomized smoothing. In: Proceedings of the 39th International Conference on Machine Learning. Vol 162. ML Research Press; 2022:20697-20743.
[Published Version]
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| arXiv
Grants
3 Publications
2023 |
In Press |
Conference Paper |
IST-REx-ID: 14921 |
Súkeník P, Mondelli M, Lampert C. Deep neural collapse is provably optimal for the deep unconstrained features model. In: 37th Annual Conference on Neural Information Processing Systems.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
2022 |
Submitted |
Preprint |
IST-REx-ID: 12662 |
Súkeník P, Lampert C. Generalization in Multi-objective machine learning. arXiv. doi:10.48550/arXiv.2208.13499
[Preprint]
View
| DOI
| Download Preprint (ext.)
| arXiv
2022 |
Published |
Conference Paper |
IST-REx-ID: 12664 |
Súkeník P, Kuvshinov A, Günnemann S. Intriguing properties of input-dependent randomized smoothing. In: Proceedings of the 39th International Conference on Machine Learning. Vol 162. ML Research Press; 2022:20697-20743.
[Published Version]
View
| Files available
| arXiv