164 citations · 203 across the 6 of their papers we have counts for
4 papers · 1 filter
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…
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…
Self-training Avoids Using Spurious Features Under Domain Shift
Yining Chen, Colin Wei, Ananya Kumar +1
In unsupervised domain adaptation, existing theory focuses on situations where the source and target domains are close. In practice, conditional entropy minimization and pseudo-lab…
The Implicit and Explicit Regularization Effects of Dropout
Colin Wei, Sham Kakade, Tengyu Ma
Dropout is a widely-used regularization technique, often required to obtain state-of-the-art for a number of architectures. This work demonstrates that dropout introduces two disti…