most citedRobust Linear Discriminant Analysis Using Ratio Minimization of L1,2-Norms

2 citations · 3 across the 3 of their papers we have counts for

collaborators

8 papers

cs.CL2019

Relation-Aware Entity Alignment for Heterogeneous Knowledge Graphs

Yuting Wu, Xiao Liu, Yansong Feng +3

Entity alignment is the task of linking entities with the same real-world identity from different knowledge graphs (KGs), which has been recently dominated by embedding-based metho…

cs.LG20192 cited

Robust Linear Discriminant Analysis Using Ratio Minimization of L1,2-Norms

Feiping Nie, Hua Wang, Zheng Wang +1

As one of the most popular linear subspace learning methods, the Linear Discriminant Analysis (LDA) method has been widely studied in machine learning community and applied to many…

cs.CV20191 cited

Less Memory, Faster Speed: Refining Self-Attention Module for Image Reconstruction

Zheng Wang, Jianwu Li, Ge Song +1

Self-attention (SA) mechanisms can capture effectively global dependencies in deep neural networks, and have been applied to natural language processing and image processing succes…

cs.CV2019

Illumination-Adaptive Person Re-identification

Zelong Zeng, Zhixiang Wang, Zheng Wang +3

Most person re-identification (ReID) approaches assume that person images are captured under relatively similar illumination conditions. In reality, long-term person retrieval is c…

cs.DB2019

GPU-based Efficient Join Algorithms on Hadoop

Hongzhi Wang, Ning Li, Zheng Wang +1

The growing data has brought tremendous pressure for query processing and storage, so there are many studies that focus on using GPU to accelerate join operation, which is one of t…

cs.LG2018

Representation Learning for Spatial Graphs

Zheng Wang, Ce Ju, Gao Cong +1

Recently, the topic of graph representation learning has received plenty of attention. Existing approaches usually focus on structural properties only and thus they are not suffici…