84 citations · 554 across the 60 of their papers we have counts for
10 papers · 1 filter
Copula for Instance-wise Feature Selection and Ranking
Hanyu Peng, Guanhua Fang, Ping Li
Instance-wise feature selection and ranking methods can achieve a good selection of task-friendly features for each sample in the context of neural networks. However, existing appr…
Steering Graph Neural Networks with Pinning Control
Acong Zhang, Ping Li, Guanrong Chen
In the semi-supervised setting where labeled data are largely limited, it remains to be a big challenge for message passing based graph neural networks (GNNs) to learn feature repr…
On the Overlooked Structure of Stochastic Gradients
Zeke Xie, Qian-Yuan Tang, Mingming Sun +1
Stochastic gradients closely relate to both optimization and generalization of deep neural networks (DNNs). Some works attempted to explain the success of stochastic optimization f…
Neural Network Panning: Screening the Optimal Sparse Network Before Training
Xiatao Kang, Ping Li, Jiayi Yao +1
Pruning on neural networks before training not only compresses the original models, but also accelerates the network training phase, which has substantial application value. The cu…
CGAR: Critic Guided Action Redistribution in Reinforcement Leaning
Tairan Huang, Xu Li, Hao Li +2
Training a game-playing reinforcement learning agent requires multiple interactions with the environment. Ignorant random exploration may cause a waste of time and resources. It's…
Revisiting the role of heterophily in graph representation learning: An edge classification perspective
Jincheng Huang, Ping Li, Rui Huang +2
Graph representation learning aim at integrating node contents with graph structure to learn nodes/graph representations. Nevertheless, it is found that many existing graph learnin…