2 papers
cs.LG2026
The Implicit Bias of Adam and Muon on Smooth Homogeneous Neural Networks
Eitan Gronich, Gal Vardi
We study the implicit bias of momentum-based optimizers on smooth homogeneous models. We show that \textit{momentum steepest descent} algorithms like Muon (spectral norm), Momentum…
cs.LG2025
Querying Kernel Methods Suffices for Reconstructing their Training Data
Daniel Barzilai, Yuval Margalit, Eitan Gronich +3
Over-parameterized models have raised concerns about their potential to memorize training data, even when achieving strong generalization. The privacy implications of such memoriza…