Donghao Li

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2 papers · 1 filter

stat.ML2023

Random Smoothing Regularization in Kernel Gradient Descent Learning

Liang Ding, Tianyang Hu, Jiahang Jiang +3

Random smoothing data augmentation is a unique form of regularization that can prevent overfitting by introducing noise to the input data, encouraging the model to learn more gener…

stat.ML2019

$S^{2}$ -LBI: Stochastic Split Linearized Bregman Iterations for Parsimonious Deep Learning

Yanwei Fu, Donghao Li, Xinwei Sun +3

This paper proposes a novel Stochastic Split Linearized Bregman Iteration ( $S^{2}$ -LBI) algorithm to efficiently train the deep network. The $S^{2}$ -LBI introduces an iterative reg…

Random Smoothing Regularization in Kernel Gradient Descent Learning

S2-LBI: Stochastic Split Linearized Bregman Iterations for Parsimonious Deep Learning

$S^{2}$ -LBI: Stochastic Split Linearized Bregman Iterations for Parsimonious Deep Learning