4 citations · 8 across the 3 of their papers we have counts for
3 papers
cs.LG2023★ 1 cited
Beyond Implicit Bias: The Insignificance of SGD Noise in Online Learning
Nikhil Vyas, Depen Morwani, Rosie Zhao +3
The success of SGD in deep learning has been ascribed by prior works to the implicit bias induced by finite batch sizes ("SGD noise"). While prior works focused on offline learning…
cs.LG2023★ 3 cited
Feature-Learning Networks Are Consistent Across Widths At Realistic Scales
Nikhil Vyas, Alexander Atanasov, Blake Bordelon +3
We study the effect of width on the dynamics of feature-learning neural networks across a variety of architectures and datasets. Early in training, wide neural networks trained on…
cs.LG2022★ 4 cited
Limitations of the NTK for Understanding Generalization in Deep Learning
Nikhil Vyas, Yamini Bansal, Preetum Nakkiran
The ``Neural Tangent Kernel'' (NTK) (Jacot et al 2018), and its empirical variants have been proposed as a proxy to capture certain behaviors of real neural networks. In this work,…