In this paper, we propose a semi-supervised learning (SSL) algorithm based on local and global regularization. In the local regularization part, our algorithm constructs a regular...
This paper describes a novel approach for obtaining semantic interoperability in a bottom-up, semi-automatic manner without relying on pre-existing, global semantic models. We ass...
A new large margin classifier, named MaxiMin Margin Machine (M4 ) is proposed in this paper. This new classifier is constructed based on both a "local" and a "globa...
Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. ...
In this paper, we define a simple but scalable framework for peer-to-peer data sharing systems, in which the problem of answering queries over a network of semantically related p...
Existing feature extraction methods explore either global statistical or local geometric information underlying the data. In this paper, we propose a general framework to learn fea...
Shuang-Hong Yang, Hongyuan Zha, Shaohua Kevin Zhou...