Privacy for free in the overparameterized regime
S. Bombari, M. Mondelli, Proceedings of the National Academy of Sciences 122 (2025).

Towards understanding the word sensitivity of attention layers: A study via random features
S. Bombari, M. Mondelli, in:, 41st International Conference on Machine Learning, ML Research Press, 2024, pp. 4300–4328.

How spurious features are memorized: Precise analysis for random and NTK features
S. Bombari, M. Mondelli, in:, 41st International Conference on Machine Learning, ML Research Press, 2024, pp. 4267–4299.

Beyond the universal law of robustness: Sharper laws for random features and neural tangent kernels
S. Bombari, S. Kiyani, M. Mondelli, in:, Proceedings of the 40th International Conference on Machine Learning, ML Research Press, 2023, pp. 2738–2776.

Towards differential relational privacy and its use in question answering
S. Bombari, A. Achille, Z. Wang, Y.-X. Wang, Y. Xie, K.Y. Singh, S. Appalaraju, V. Mahadevan, S. Soatto, ArXiv (n.d.).

Memorization and optimization in deep neural networks with minimum over-parameterization
S. Bombari, M.H. Amani, M. Mondelli, in:, 36th Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2022, pp. 7628–7640.

Sharp asymptotics on the compression of two-layer neural networks
M.H. Amani, S. Bombari, M. Mondelli, R. Pukdee, S. Rini, IEEE Information Theory Workshop (2022) 588–593.