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Maria Matveev

2 accepted papers

2026

Conflicting Biases at the Edge of Stability: Norm versus Sharpness Regularization

ICML 2026poster

The remarkable generalization properties of overparameterized networks are often attributed to implicit biases, such as norm minimization at small learning rates and low sharpness in the Edge-of-Stability regime. In this work, we argue that a comprehensive understanding of the generalization perform…

Cited by 0SourceScholar
2026

ExPLAIND: Unifying Model, Data, and Training Attribution to Study Model Behavior

ICML 2026poster

Post-hoc interpretability methods typically attribute a model’s behavior to its components, data, or training trajectory in isolation. This leads to explanations that lack a unified view and may miss key interactions. While combining existing methods or applying them at different training stages off…

Cited by 0SourceScholar