10 citations · 20 across the 5 of their papers we have counts for
5 papers
Convergence Analysis for Restarted Anderson Mixing and Beyond
Fuchao Wei, Chenglong Bao, Yang Liu +1
Anderson mixing (AM) is a classical method that can accelerate fixed-point iterations by exploring historical information. Despite the successful application of AM in scientific co…
A Closer Look at the Adversarial Robustness of Deep Equilibrium Models
Zonghan Yang, Tianyu Pang, Yang Liu
Deep equilibrium models (DEQs) refrain from the traditional layer-stacking paradigm and turn to find the fixed point of a single layer. DEQs have achieved promising performance on…
On Robust Prefix-Tuning for Text Classification
Zonghan Yang, Yang Liu
Recently, prefix-tuning has gained increasing attention as a parameter-efficient finetuning method for large-scale pretrained language models. The method keeps the pretrained model…
Stochastic Anderson Mixing for Nonconvex Stochastic Optimization
Fuchao Wei, Chenglong Bao, Yang Liu
Anderson mixing (AM) is an acceleration method for fixed-point iterations. Despite its success and wide usage in scientific computing, the convergence theory of AM remains unclear,…
Interpolation between Residual and Non-Residual Networks
Zonghan Yang, Yang Liu, Chenglong Bao +1
Although ordinary differential equations (ODEs) provide insights for designing network architectures, its relationship with the non-residual convolutional neural networks (CNNs) is…