activity
20182020
most citedDynamic Graph Correlation Learning for Disease Diagnosis with Incomplete Labels

1 citations · 1 across the 2 of their papers we have counts for

collaborators

8 papers

cs.CR2020

Local Generalization and Bucketization Technique for Personalized Privacy Preservation

Boyu Li, Kun He, Geng Sun

Anonymization technique has been extensively studied and widely applied for privacy-preserving data publishing. In most previous approaches, a microdata table consists of three cat…

cs.CV20201 cited

Dynamic Graph Correlation Learning for Disease Diagnosis with Incomplete Labels

Daizong Liu, Shuangjie Xu, Pan Zhou +3

Disease diagnosis on chest X-ray images is a challenging multi-label classification task. Previous works generally classify the diseases independently on the input image without co…

cs.SI2020

Sparse Nonnegative Matrix Factorization for Multiple Local Community Detection

Dany Kamuhanda, Meng Wang, Kun He

Local community detection consists of finding a group of nodes closely related to the seeds, a small set of nodes of interest. Such group of nodes are densely connected or have a h…

cs.SI2020

Hidden Community Detection on Two-layer Stochastic Models: a Theoretical Perspective

Jialu Bao, Kun He, Xiaodong Xin +2

Hidden community is a new graph-theoretical concept recently proposed [4], in which the authors also propose a meta-approach called HICODE (Hidden Community Detection) for detectin…

cs.CV2019

Single Image Reflection Removal through Cascaded Refinement

Chao Li, Yixiao Yang, Kun He +2

We address the problem of removing undesirable reflections from a single image captured through a glass surface, which is an ill-posed, challenging but practically important proble…

q-bio.MN2019

Hierarchical hidden community detection for protein complex prediction

Chao Li, Kun He, Guangshuai Liu +1

Motivation: Discovering functional modules in protein-protein interaction (PPI) networks by optimization methods remains a longstanding challenge in biology. Traditional algorithms…