Recently the problem of dimensionality reduction has received a lot of interests in many fields of information processing. We consider the case where data is sampled from a low d...
Many approaches to active learning involve training one classifier by periodically choosing new data points about which the classifier has the least confidence, but designing a co...
In this paper, we propose a semi-supervised framework for learning a weighted Euclidean subspace, where the best clustering can be achieved. Our approach capitalizes on user-const...
Maria Halkidi, Dimitrios Gunopulos, Nitin Kumar, M...
Dependency analysis of natural language gives rise to non-projective structures. The constraint of well-nestedness on dependency trees has been recently shown to give a good fit ...
Transductive inference on graphs such as label propagation algorithms is receiving a lot of attention. In this paper, we address a label propagation problem on multiple networks a...