A structural similarity kernel is presented in this paper for SVM learning, especially for learning with imbalanced datasets. Kernels in SVM are usually pairwise, comparing the sim...
The space of images is known to be a non-linear subspace that is difficult to model. This paper derives an algorithm that walks within this space. We seek a manifold through the ...
Graph-theoretic aggregation problems have been considered both in OLAP (grid graph) and XML (tree). This paper gives new results for MIN aggregation in a tree, where we want the M...
As more and more multi-tier services are developed from commercial components or heterogeneous middleware without the source code available, both developers and administrators nee...
Zhihong Zhang, Jianfeng Zhan, Yong Li, Lei Wang, D...
Subspace clustering (also called projected clustering) addresses the problem that different sets of attributes may be relevant for different clusters in high dimensional feature sp...