10 citations · 26 across the 20 of their papers we have counts for
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cs.CV2022★ 3 cited
Efficient Generalization Improvement Guided by Random Weight Perturbation
Tao Li, Weihao Yan, Zehao Lei +4
To fully uncover the great potential of deep neural networks (DNNs), various learning algorithms have been developed to improve the model's generalization ability. Recently, sharpn…
cs.LG2022★ 2 cited
Multi-head Ensemble of Smoothed Classifiers for Certified Robustness
Kun Fang, Qinghua Tao, Yingwen Wu +3
Randomized Smoothing (RS) is a promising technique for certified robustness, and recently in RS the ensemble of multiple Deep Neural Networks (DNNs) has shown state-of-the-art perf…
cs.LG2022
Trainable Weight Averaging: Accelerating Training and Improving Generalization
Tao Li, Zhehao Huang, Yingwen Wu +4
Weight averaging is a widely used technique for accelerating training and improving the generalization of deep neural networks (DNNs). While existing approaches like stochastic wei…