Simone Bombari
7 Publications
2025 | Published | Journal Article | IST-REx-ID: 19627 |
Bombari S, Mondelli M. Privacy for free in the overparameterized regime. Proceedings of the National Academy of Sciences. 2025;122(15). doi:10.1073/pnas.2423072122
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2024 | Published | Conference Paper | IST-REx-ID: 18973 |
Bombari S, Mondelli M. Towards understanding the word sensitivity of attention layers: A study via random features. In: 41st International Conference on Machine Learning. Vol 235. ML Research Press; 2024:4300-4328.
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| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 18972 |
Bombari S, Mondelli M. How spurious features are memorized: Precise analysis for random and NTK features. In: 41st International Conference on Machine Learning. Vol 235. ML Research Press; 2024:4267-4299.
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2023 | Published | Conference Paper | IST-REx-ID: 12859 |
Bombari S, Kiyani S, Mondelli M. Beyond the universal law of robustness: Sharper laws for random features and neural tangent kernels. In: Proceedings of the 40th International Conference on Machine Learning. Vol 202. ML Research Press; 2023:2738-2776.
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| arXiv
2022 | Submitted | Preprint | IST-REx-ID: 12860 |
Bombari S, Achille A, Wang Z, et al. Towards differential relational privacy and its use in question answering. arXiv. doi:10.48550/arXiv.2203.16701
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2022 | Published | Conference Paper | IST-REx-ID: 12537 |
Bombari S, Amani MH, Mondelli M. Memorization and optimization in deep neural networks with minimum over-parameterization. In: 36th Conference on Neural Information Processing Systems. Vol 35. Neural Information Processing Systems Foundation; 2022:7628-7640.
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2022 | Published | Journal Article | IST-REx-ID: 12538 |
Amani MH, Bombari S, Mondelli M, Pukdee R, Rini S. Sharp asymptotics on the compression of two-layer neural networks. IEEE Information Theory Workshop. 2022:588-593. doi:10.1109/ITW54588.2022.9965870
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7 Publications
2025 | Published | Journal Article | IST-REx-ID: 19627 |
Bombari S, Mondelli M. Privacy for free in the overparameterized regime. Proceedings of the National Academy of Sciences. 2025;122(15). doi:10.1073/pnas.2423072122
[Published Version]
View
| Files available
| DOI
| WoS
| PubMed | Europe PMC
| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 18973 |
Bombari S, Mondelli M. Towards understanding the word sensitivity of attention layers: A study via random features. In: 41st International Conference on Machine Learning. Vol 235. ML Research Press; 2024:4300-4328.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 18972 |
Bombari S, Mondelli M. How spurious features are memorized: Precise analysis for random and NTK features. In: 41st International Conference on Machine Learning. Vol 235. ML Research Press; 2024:4267-4299.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 12859 |
Bombari S, Kiyani S, Mondelli M. Beyond the universal law of robustness: Sharper laws for random features and neural tangent kernels. In: Proceedings of the 40th International Conference on Machine Learning. Vol 202. ML Research Press; 2023:2738-2776.
[Preprint]
View
| Files available
| Download Preprint (ext.)
| arXiv
2022 | Submitted | Preprint | IST-REx-ID: 12860 |
Bombari S, Achille A, Wang Z, et al. Towards differential relational privacy and its use in question answering. arXiv. doi:10.48550/arXiv.2203.16701
[Preprint]
View
| DOI
| Download Preprint (ext.)
| arXiv
2022 | Published | Conference Paper | IST-REx-ID: 12537 |
Bombari S, Amani MH, Mondelli M. Memorization and optimization in deep neural networks with minimum over-parameterization. In: 36th Conference on Neural Information Processing Systems. Vol 35. Neural Information Processing Systems Foundation; 2022:7628-7640.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
2022 | Published | Journal Article | IST-REx-ID: 12538 |
Amani MH, Bombari S, Mondelli M, Pukdee R, Rini S. Sharp asymptotics on the compression of two-layer neural networks. IEEE Information Theory Workshop. 2022:588-593. doi:10.1109/ITW54588.2022.9965870
[Preprint]
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| arXiv