103 citations · 139 across the 9 of their papers we have counts for
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cs.LG2020★ 12 cited
A Unifying View on Implicit Bias in Training Linear Neural Networks
Chulhee Yun, Shankar Krishnan, Hossein Mobahi
We study the implicit bias of gradient flow (i.e., gradient descent with infinitesimal step size) on linear neural network training. We propose a tensor formulation of neural netwo…
cs.LG2020★ 5 cited
Weak and Strong Gradient Directions: Explaining Memorization, Generalization, and Hardness of Examples at Scale
Piotr Zielinski, Shankar Krishnan, Satrajit Chatterjee
Coherent Gradients (CGH) is a recently proposed hypothesis to explain why over-parameterized neural networks trained with gradient descent generalize well even though they have suf…