18 citations · 19 across the 2 of their papers we have counts for
3 papers
cs.LG2020★ 1 cited
Meta-learning Transferable Representations with a Single Target Domain
Hong Liu, Jeff Z. HaoChen, Colin Wei +1
Recent works found that fine-tuning and joint training---two popular approaches for transfer learning---do not always improve accuracy on downstream tasks. First, we aim to underst…
cs.LG2020★ 18 cited
Shape Matters: Understanding the Implicit Bias of the Noise Covariance
Jeff Z. HaoChen, Colin Wei, Jason D. Lee +1
The noise in stochastic gradient descent (SGD) provides a crucial implicit regularization effect for training overparameterized models. Prior theoretical work largely focuses on sp…
math.OC2018
Random Shuffling Beats SGD after Finite Epochs
Jeff Z. HaoChen, Suvrit Sra
A long-standing problem in the theory of stochastic gradient descent (SGD) is to prove that its without-replacement version RandomShuffle converges faster than the usual with-repla…