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52 Publications
2023 | Conference Paper | IST-REx-ID: 14921 | 
P. Súkeník, M. Mondelli, and C. Lampert, “Deep neural collapse is provably optimal for the deep unconstrained features model,” in 37th Annual Conference on Neural Information Processing Systems, New Orleans, LA, United States.
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| arXiv
2023 | Conference Paper | IST-REx-ID: 14924 |
D. Wu, V. Kungurtsev, and M. Mondelli, “Mean-field analysis for heavy ball methods: Dropout-stability, connectivity, and global convergence,” in Transactions on Machine Learning Research, 2023.
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| arXiv
2023 | Conference Paper | IST-REx-ID: 14923 |
T. Fu, Y. Liu, J. Barbier, M. Mondelli, S. Liang, and T. Hou, “Mismatched estimation of non-symmetric rank-one matrices corrupted by structured noise,” in Proceedings of 2023 IEEE International Symposium on Information Theory, Taipei, Taiwan.
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| arXiv
2023 | Conference Paper | IST-REx-ID: 14922 |
A. R. Esposito and M. Mondelli, “Concentration without independence via information measures,” in Proceedings of 2023 IEEE International Symposium on Information Theory, Taipei, Taiwan, 2023, pp. 400–405.
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| arXiv
2022 | Journal Article | IST-REx-ID: 11420 |
A. Shevchenko, V. Kungurtsev, and M. Mondelli, “Mean-field analysis of piecewise linear solutions for wide ReLU networks,” Journal of Machine Learning Research, vol. 23, no. 130. Journal of Machine Learning Research, pp. 1–55, 2022.
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| arXiv