Insufficiency of labeled training data is a major obstacle for automatically annotating large-scale video databases with semantic concepts. Existing semi-supervised learning algorithms based on parametric models try to tackle this issue by incorpora
Graph-based Semi-Supervised Learning (SSL) methods are the widely used SSL methods due to their high accuracy. They can well meet the manifold assumption with high computational cost, but don't meet the cluster assumption. In this paper, we propose a
