2 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.LG2020
Regularizing Semi-supervised Graph Convolutional Networks with a Manifold Smoothness Loss
Qilin Li, Wanquan Liu, Ling Li
Existing graph convolutional networks focus on the neighborhood aggregation scheme. When applied to semi-supervised learning, they often suffer from the overfitting problem as the…
cs.CV2019★ 1 cited
A Novel Euler's Elastica based Segmentation Approach for Noisy Images via using the Progressive Hedging Algorithm
Lu Tan, Ling Li, Wanquan Liu +2
Euler's Elastica based unsupervised segmentation models have strong capability of completing the missing boundaries for existing objects in a clean image, but they are not working…
cs.CV2019★ 2 cited
Semi-supervised Learning on Graph with an Alternating Diffusion Process
Qilin Li, Senjian An, Ling Li +1
Graph-based semi-supervised learning usually involves two separate stages, constructing an affinity graph and then propagating labels for transductive inference on the graph. It is…