35 citations · 109 across the 9 of their papers we have counts for
Showing 2018Show all
3 papers · 1 filter
cs.LG2018★ 8 cited
An Efficient Approach to Informative Feature Extraction from Multimodal Data
Lichen Wang, Jiaxiang Wu, Shao-Lun Huang +4
One primary focus in multimodal feature extraction is to find the representations of individual modalities that are maximally correlated. As a well-known measure of dependence, the…
cs.CV2018★ 35 cited
Error Compensated Quantized SGD and its Applications to Large-scale Distributed Optimization
Jiaxiang Wu, Weidong Huang, Junzhou Huang +1
Large-scale distributed optimization is of great importance in various applications. For data-parallel based distributed learning, the inter-node gradient communication often becom…
math.OC2018★ 32 cited
Double Quantization for Communication-Efficient Distributed Optimization
Yue Yu, Jiaxiang Wu, Longbo Huang
Modern distributed training of machine learning models suffers from high communication overhead for synchronizing stochastic gradients and model parameters. In this paper, to reduc…