This paper proposes a novel hierarchical learning strategy to deal with the data sparseness problem in relation extraction by modeling the commonality among related classes. For e...
The usage and service options of a pubic network generally differ from a private (enterprise or home) network and consequently, the two networks are often configured differently. ...
Density estimation with Gaussian Mixture Models is a popular generative technique used also for clustering. We develop a framework to incorporate side information in the form of e...
Constructing three-dimensional model from two-dimensional images is an old problem in the area of computer vision. There are many publications and our approach is specifically des...
Mining frequent itemsets is a popular method for finding associated items in databases. For this method, support, the co-occurrence frequency of the items which form an associatio...