For large scale automatic semantic video characterization, it is necessary to learn and model a large number of semantic concepts. But a major obstacle to this is the insufficienc...
This paper analyzes the performance of semisupervised learning of mixture models. We show that unlabeled data can lead to an increase in classification error even in situations wh...
Fabio Gagliardi Cozman, Ira Cohen, Marcelo Cesar C...
In this paper, we address the scalability issue plaguing graph-based semi-supervised learning via a small number of anchor points which adequately cover the entire point cloud. Cr...
We consider a framework for semi-supervised learning using spectral decomposition-based unsupervised kernel design. We relate this approach to previously proposed semi-supervised l...
This paper proposes a novel algorithm for semisupervised learning. This algorithm learns graph cuts that maximize the margin with respect to the labels induced by the harmonic fun...
Branislav Kveton, Michal Valko, Ali Rahimi, Ling H...