212 citations · 376 across the 15 of their papers we have counts for
Showing stat.MLShow all
3 papers · 1 filter
stat.ML2023
How Many Pretraining Tasks Are Needed for In-Context Learning of Linear Regression?
Jingfeng Wu, Difan Zou, Zixiang Chen +3
Transformers pretrained on diverse tasks exhibit remarkable in-context learning (ICL) capabilities, enabling them to solve unseen tasks solely based on input contexts without adjus…
stat.ML2023
Per-Example Gradient Regularization Improves Learning Signals from Noisy Data
Xuran Meng, Yuan Cao, Difan Zou
Gradient regularization, as described in \citet{barrett2021implicit}, is a highly effective technique for promoting flat minima during gradient descent. Empirical evidence suggests…
stat.ML2018
Stochastic Variance-Reduced Hamilton Monte Carlo Methods
Difan Zou, Pan Xu, Quanquan Gu
We propose a fast stochastic Hamilton Monte Carlo (HMC) method, for sampling from a smooth and strongly log-concave distribution. At the core of our proposed method is a variance r…