Although different graph inference methods exist, they are restricted to learning from either smooth graph signals or with simple additive Gaussian noise. Other types of noisy data, such as discrete ...

Graph-based semi-supervised learning (GSSL) has long been a research focus. Traditional methods are generally shallow learners, based on the cluster assumption.

Our results demonstrate that the proposed method significantly outperforms traditional machine learning and convolution neural network approaches, highlighting its effectiveness in large-scale ...