3 accepted papers
Graph representation learning is fundamental for analyzing graph-structured data. Exploring invariant graph representations remains a challenge for most existing graph representation learning methods. In this paper, we propose a cross-view graph consistency learning (CGCL) method that learns invaria…
Multiview clustering (MVC) aims to reveal the underlying structure of multiview data by categorizing data samples into clusters. Deep learning-based methods exhibit strong feature learning capabilities on large-scale datasets. For most existing deep MVC methods, exploring the invariant representatio…
A novel unsupervised sparse component extraction algorithm for diagnosing micro defects in thermography imaging system is presented. The approach is optimized under Variational Bayesian framework, which is fully automated and does not require manual selection of the parameters in the solution. An in…