With advances in information acquisition technologies, multi-view data become ubiquitous. Multi-view learning has thus become more and more popular in machine learning and data mining fields. Multi-view unsupervised or semi-supervised learning, such as co-training, co-regularization has gained considerable attention. Although recently, multi-view clustering (MVC) methods have been developed rap...

This paper addresses the problem of unsupervised object localization in an image. Unlike previous supervised and weakly supervised algorithms that require bounding box or image level annotations for training classifiers in order to learn features representing the object, we propose a simple yet effective technique for localization using iterative spectral clustering. This iterative spectral clu...

• A graph learning framework, which captures both the global and local structure in data, is proposed. Theoretical analysis builds connections of our model to k-means, spectral clustering, kernel k-means. Extensions semi-supervised classification multiple are presented. Graphs have become increasingly popular modeling structures interactions a wide variety problems during last decade. Graph-bas...