Sharp asymptotics on the compression of two-layer neural networks. - Mohammad Hossein Amani; Simone Bombari; Marco Mondelli; Rattana Pukdee; Stefano Rini (ITW, 2022)

Memorization and Optimization in Deep Neural Networks with Minimum Over-parameterization. - Simone Bombari; Mohammad Hossein Amani; Marco Mondelli (NeurIPS, 2022)

Towards Differential Relational Privacy and its use in Question Answering. - Simone Bombari; Alessandro Achille; Zijian Wang 002; Yu-Xiang Wang 003; Yusheng Xie; Kunwar Yashraj Singh; Srikar Appalaraju; Vijay Mahadevan; Stefano Soatto (CoRR, 2022)

Beyond the Universal Law of Robustness: Sharper Laws for Random Features and Neural Tangent Kernels. - Simone Bombari; Shayan Kiyani; Marco Mondelli (ICML, 2023)

Stability, Generalization and Privacy: Precise Analysis for Random and NTK Features. - Simone Bombari; Marco Mondelli (CoRR, 2023)

How Spurious Features are Memorized: Precise Analysis for Random and NTK Features. - Simone Bombari; Marco Mondelli (ICML, 2024)

Towards Understanding the Word Sensitivity of Attention Layers: A Study via Random Features. - Simone Bombari; Marco Mondelli (ICML, 2024)

DP-KAN: Differentially Private Kolmogorov-Arnold Networks. - Nikita P. Kalinin; Simone Bombari; Hossein Zakerinia; Christoph H. Lampert (CoRR, 2024)

Privacy for Free in the Over-Parameterized Regime. - Simone Bombari; Marco Mondelli (CoRR, 2024)

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization. - Simone Bombari; Marco Mondelli (CoRR, 2025)

Better Rates for Private Linear Regression in the Proportional Regime via Aggressive Clipping. - Simone Bombari; Inbar Seroussi; Marco Mondelli (CoRR, 2025)