5 citations · 7 across the 3 of their papers we have counts for
3 papers
cs.LG2022★ 5 cited
Revisiting Optimal Convergence Rate for Smooth and Non-convex Stochastic Decentralized Optimization
Kun Yuan, Xinmeng Huang, Yiming Chen +3
Decentralized optimization is effective to save communication in large-scale machine learning. Although numerous algorithms have been proposed with theoretical guarantees and empir…
cs.CV2022★ 1 cited
Deep Class Incremental Learning from Decentralized Data
Xiaohan Zhang, Songlin Dong, Jinjie Chen +3
In this paper, we focus on a new and challenging decentralized machine learning paradigm in which there are continuous inflows of data to be addressed and the data are stored in mu…
cs.CV2019★ 1 cited
Scale Calibrated Training: Improving Generalization of Deep Networks via Scale-Specific Normalization
Zhuoran Yu, Aojun Zhou, Yukun Ma +3
Standard convolutional neural networks(CNNs) require consistent image resolutions in both training and testing phase. However, in practice, testing with smaller image sizes is nece…