activity
20182022
most citedHow to Close Sim-Real Gap? Transfer with Segmentation!

6 citations · 26 across the 8 of their papers we have counts for

collaborators

13 papers

cs.CL20222 cited

Type Information Utilized Event Detection via Multi-Channel GNNs in Electrical Power Systems

Qian Li, Jianxin Li, Lihong Wang +6

Event detection in power systems aims to identify triggers and event types, which helps relevant personnel respond to emergencies promptly and facilitates the optimization of power…

cs.LG20224 cited

Heterogeneous Graph Neural Network for Privacy-Preserving Recommendation

Yuecen Wei, Xingcheng Fu, Qingyun Sun +4

Social networks are considered to be heterogeneous graph neural networks (HGNNs) with deep learning technological advances. HGNNs, compared to homogeneous data, absorb various aspe…

cs.LG2022

Curvature Graph Generative Adversarial Networks

Jianxin Li, Xingcheng Fu, Qingyun Sun +4

Generative adversarial network (GAN) is widely used for generalized and robust learning on graph data. However, for non-Euclidean graph data, the existing GAN-based graph represent…

cs.IT20212 cited

Convex Sparse Blind Deconvolution

Qingyun Sun, David Donoho

In the blind deconvolution problem, we observe the convolution of an unknown filter and unknown signal and attempt to reconstruct the filter and signal. The problem seems impossibl…

cs.LG20213 cited

A Robust and Generalized Framework for Adversarial Graph Embedding

Jianxin Li, Xingcheng Fu, Hao Peng +5

Graph embedding is essential for graph mining tasks. With the prevalence of graph data in real-world applications, many methods have been proposed in recent years to learn high-qua…

cs.LG20214 cited

A Recipe for Global Convergence Guarantee in Deep Neural Networks

Kenji Kawaguchi, Qingyun Sun

Existing global convergence guarantees of (stochastic) gradient descent do not apply to practical deep networks in the practical regime of deep learning beyond the neural tangent k…