23 citations · 30 across the 3 of their papers we have counts for
3 papers · 1 filter
GPN: A Joint Structural Learning Framework for Graph Neural Networks
Qianggang Ding, Deheng Ye, Tingyang Xu +1
Graph neural networks (GNNs) have been applied into a variety of graph tasks. Most existing work of GNNs is based on the assumption that the given graph data is optimal, while it i…
Risk-Averse Trust Region Optimization for Reward-Volatility Reduction
Lorenzo Bisi, Luca Sabbioni, Edoardo Vittori +2
In real-world decision-making problems, for instance in the fields of finance, robotics or autonomous driving, keeping uncertainty under control is as important as maximizing expec…
Adaptive Regularization of Labels
Qianggang Ding, Sifan Wu, Hao Sun +2
Recently, a variety of regularization techniques have been widely applied in deep neural networks, such as dropout, batch normalization, data augmentation, and so on. These methods…