Peter Súkeník

Graduate School
Mondelli Group
Lampert Group

6 Publications

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[6]
2024 | Epub ahead of print | Journal Article | IST-REx-ID: 12662 | OA
Generalization in multi-objective machine learning
P. Súkeník, C. Lampert, Neural Computing and Applications (2024).
[Published Version] View | DOI | Download Published Version (ext.) | arXiv
 
[5]
2024 | Published | Conference Paper | IST-REx-ID: 18890 | OA
Average gradient outer product as a mechanism for deep neural collapse
D. Beaglehole, P. Súkeník, M. Mondelli, M. Belkin, in:, 38th Annual Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2024.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[4]
2024 | Published | Conference Paper | IST-REx-ID: 18891 | OA
Neural collapse versus low-rank bias: Is deep neural collapse really optimal?
P. Súkeník, C. Lampert, M. Mondelli, in:, 38th Annual Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2024.
[Published Version] View | Files available
 
[3]
2023 | Published | Conference Paper | IST-REx-ID: 14921 | OA
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, 2023.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[2]
2022 | Published | Conference Paper | IST-REx-ID: 18876 | OA
The unreasonable effectiveness of fully-connected layers for low-data regimes
Kocsis, Peter, The unreasonable effectiveness of fully-connected layers for low-data regimes. 36th Conference on Neural Information Processing Systems 35. 2022
[Published Version] View | Files available | arXiv
 
[1]
2022 | Published | Conference Paper | IST-REx-ID: 12664 | OA
Intriguing properties of input-dependent randomized smoothing
Súkeník, Peter, Intriguing properties of input-dependent randomized smoothing. Proceedings of the 39th International Conference on Machine Learning 162. 2022
[Published Version] View | Files available | arXiv
 
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6 Publications

Mark all

[6]
2024 | Epub ahead of print | Journal Article | IST-REx-ID: 12662 | OA
Generalization in multi-objective machine learning
P. Súkeník, C. Lampert, Neural Computing and Applications (2024).
[Published Version] View | DOI | Download Published Version (ext.) | arXiv
 
[5]
2024 | Published | Conference Paper | IST-REx-ID: 18890 | OA
Average gradient outer product as a mechanism for deep neural collapse
D. Beaglehole, P. Súkeník, M. Mondelli, M. Belkin, in:, 38th Annual Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2024.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[4]
2024 | Published | Conference Paper | IST-REx-ID: 18891 | OA
Neural collapse versus low-rank bias: Is deep neural collapse really optimal?
P. Súkeník, C. Lampert, M. Mondelli, in:, 38th Annual Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2024.
[Published Version] View | Files available
 
[3]
2023 | Published | Conference Paper | IST-REx-ID: 14921 | OA
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, 2023.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[2]
2022 | Published | Conference Paper | IST-REx-ID: 18876 | OA
The unreasonable effectiveness of fully-connected layers for low-data regimes
Kocsis, Peter, The unreasonable effectiveness of fully-connected layers for low-data regimes. 36th Conference on Neural Information Processing Systems 35. 2022
[Published Version] View | Files available | arXiv
 
[1]
2022 | Published | Conference Paper | IST-REx-ID: 12664 | OA
Intriguing properties of input-dependent randomized smoothing
Súkeník, Peter, Intriguing properties of input-dependent randomized smoothing. Proceedings of the 39th International Conference on Machine Learning 162. 2022
[Published Version] View | Files available | arXiv
 
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