A Kernel Perspective of Skip Connections in Convolutional Networks. - Daniel Barzilai; Amnon Geifman; Meirav Galun; Ronen Basri (ICLR, 2023)

Generalization in Kernel Regression Under Realistic Assumptions. - Daniel Barzilai; Ohad Shamir (ICML, 2024)

Simple Relative Deviation Bounds for Covariance and Gram Matrices. - Daniel Barzilai; Ohad Shamir (CoRR, 2024)

Controlling the Inductive Bias of Wide Neural Networks by Modifying the Kernel's Spectrum. - Amnon Geifman; Daniel Barzilai; Ronen Basri; Meirav Galun (Trans. Mach. Learn. Res., 2024)

Overfitting Regimes of Nadaraya-Watson Interpolators. - Daniel Barzilai; Guy Kornowski; Ohad Shamir (CoRR, 2025)

Querying Kernel Methods Suffices for Reconstructing their Training Data. - Daniel Barzilai; Yuval Margalit; Eitan Gronich; Gilad Yehudai; Meirav Galun; Ronen Basri (CoRR, 2025)

When Models Don't Collapse: On the Consistency of Iterative MLE. - Daniel Barzilai; Ohad Shamir (CoRR, 2025)