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Kevin Kögler

Peter Sukenik

Aleksandr Shevchenko

Yihan Zhang

Al Depope

Diyuan Wu

Marco Mondelli

Amedeo Esposito

Simone Bombari

2023 | 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

2023 | Conference Paper | IST-REx-ID: 14924 |

Mean-field analysis for heavy ball methods: Dropout-stability, connectivity, and global convergence
D. Wu, V. Kungurtsev, M. Mondelli, in:, Transactions on Machine Learning Research, ML Research Press, 2023.

[Published Version] View | Download Published Version (ext.) | arXiv

2023 | Conference Paper | IST-REx-ID: 14923 |

Mismatched estimation of non-symmetric rank-one matrices corrupted by structured noise
T. Fu, Y. Liu, J. Barbier, M. Mondelli, S. Liang, T. Hou, in:, Proceedings of 2023 IEEE International Symposium on Information Theory, IEEE, n.d.

[Preprint] View | DOI | Download Preprint (ext.) | arXiv

2023 | Conference Paper | IST-REx-ID: 14922 |

Concentration without independence via information measures
A.R. Esposito, M. Mondelli, in:, Proceedings of 2023 IEEE International Symposium on Information Theory, IEEE, 2023, pp. 400–405.

[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv

2022 | Journal Article | IST-REx-ID: 11420 |

Mean-field analysis of piecewise linear solutions for wide ReLU networks
A. Shevchenko, V. Kungurtsev, M. Mondelli, Journal of Machine Learning Research 23 (2022) 1–55.

[Published Version] View | Files available | arXiv

Mondelli Group