2 papers
cs.LG2024
Training a Label-Noise-Resistant GNN with Reduced Complexity
Rui Zhao, Bin Shi, Zhiming Liang +3
Graph Neural Networks (GNNs) have been widely employed for semi-supervised node classification tasks on graphs. However, the performance of GNNs is significantly affected by label…
cs.CV2024
Estimating Noisy Class Posterior with Part-level Labels for Noisy Label Learning
Rui Zhao, Bin Shi, Jianfei Ruan +2
In noisy label learning, estimating noisy class posteriors plays a fundamental role for developing consistent classifiers, as it forms the basis for estimating clean class posterio…