Kernel methods have been applied successfully in many data mining tasks. Subspace kernel learning was recently proposed to discover an effective low-dimensional subspace of a kern...
Jianhui Chen, Shuiwang Ji, Betul Ceran, Qi Li, Min...
Various data mining applications involve data objects of multiple types that are related to each other, which can be naturally formulated as a k-partite graph. However, the resear...
Bo Long, Xiaoyun Wu, Zhongfei (Mark) Zhang, Philip...
Several recent papers have focused on OLAP over imprecise data, where each fact can be a region, instead of a point, in a multidimensional space. They have provided a multiple-wor...
Douglas Burdick, AnHai Doan, Raghu Ramakrishnan, S...
Today's enterprise databases are large and complex, often relating hundreds of entities. Enabling ordinary users to query such databases and derive value from them has been o...
The challenge we address is to reason about projected resource usage within a hierarchical task execution framework in order to improve agent effectiveness. Specifically, we seek ...