53 citations · 68 across the 7 of their papers we have counts for
5 papers · 1 filter
Multidimensional Uncertainty-Aware Evidential Neural Networks
Yibo Hu, Yuzhe Ou, Xujiang Zhao +2
Traditional deep neural networks (NNs) have significantly contributed to the state-of-the-art performance in the task of classification under various application domains. However,…
Uncertainty Aware Semi-Supervised Learning on Graph Data
Xujiang Zhao, Feng Chen, Shu Hu +1
Thanks to graph neural networks (GNNs), semi-supervised node classification has shown the state-of-the-art performance in graph data. However, GNNs have not considered different ty…
AI Centered on Scene Fitting and Dynamic Cognitive Network
Feng Chen
This paper briefly analyzes the advantages and problems of AI mainstream technology and puts forward: To achieve stronger Artificial Intelligence, the end-to-end function calculati…
Rank-Based Multi-task Learning for Fair Regression
Chen Zhao, Feng Chen
In this work, we develop a novel fairness learning approach for multi-task regression models based on a biased training dataset, using a popular rank-based non-parametric independe…
A Primal-Dual Subgradient Approachfor Fair Meta Learning
Chen Zhao, Feng Chen, Zhuoyi Wang +1
The problem of learning to generalize to unseen classes during training, known as few-shot classification, has attracted considerable attention. Initialization based methods, such…