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