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20182025
most citedThe Anisotropic Noise in Stochastic Gradient Descent: Its Behavior of Escaping from Sharp Minima and Regularization Effects

86 citations · 120 across the 18 of their papers we have counts for

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cs.LG2025

Implicit Bias of Gradient Descent for Non-Homogeneous Deep Networks

Yuhang Cai, Kangjie Zhou, Jingfeng Wu +3

We establish the asymptotic implicit bias of gradient descent (GD) for generic non-homogeneous deep networks under exponential loss. Specifically, we characterize three key propert…

cs.LG2025

Benefits of Early Stopping in Gradient Descent for Overparameterized Logistic Regression

Jingfeng Wu, Peter Bartlett, Matus Telgarsky +1

In overparameterized logistic regression, gradient descent (GD) iterates diverge in norm while converging in direction to the maximum -margin solution -- a phenomenon known…