49 citations · 70 across the 7 of their papers we have counts for
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cs.LG2021★ 1 cited
Self-paced Principal Component Analysis
Zhao Kang, Hongfei Liu, Jiangxin Li +2
Principal Component Analysis (PCA) has been widely used for dimensionality reduction and feature extraction. Robust PCA (RPCA), under different robust distance metrics, such as l1-…
cs.LG2021★ 9 cited
Distilling Self-Knowledge From Contrastive Links to Classify Graph Nodes Without Passing Messages
Yi Luo, Aiguo Chen, Ke Yan +1
Nowadays, Graph Neural Networks (GNNs) following the Message Passing paradigm become the dominant way to learn on graphic data. Models in this paradigm have to spend extra space to…
cs.LG2020
Structured Graph Learning for Clustering and Semi-supervised Classification
Zhao Kang, Chong Peng, Qiang Cheng +4
Graphs have become increasingly popular in modeling structures and interactions in a wide variety of problems during the last decade. Graph-based clustering and semi-supervised cla…