Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel ...
Given a huge real graph, how can we derive a representative sample? There are many known algorithms to compute interesting measures (shortest paths, centrality, betweenness, etc.)...
As a fundamental data mining task, frequent pattern mining has widespread applications in many different domains. Research in frequent pattern mining has so far mostly focused on ...
Qiaozhu Mei, Dong Xin, Hong Cheng, Jiawei Han, Che...
Classification has been commonly used in many data mining projects in the financial service industry. For instance, to predict collectability of accounts receivable, a binary clas...
In today's industry, the design of software tests is mostly based on the testers' expertise, while test automation tools are limited to execution of pre-planned tests on...