In this paper we present a fast and accurate procedure called clustered low rank matrix approximation for massive graphs. The procedure involves a fast clustering of the graph and...
In this paper we present a novel technique for nearest neighbor searching dubbed neighborhood approximation. The central idea is to divide the database into compact regions repres...
In this paper, we introduce a new class of data mining problems called learning from aggregate views. In contrast to the traditional problem of learning from a single table of tra...
Bee-Chung Chen, Lei Chen 0003, Raghu Ramakrishnan,...
Popularity of mobile devices is accompanied by widespread security problems, such as MAC address spoofing in wireless networks. We propose a probabilistic approach to temporal an...
Abstract. In this paper, we present a more effective approach to clustering with eXtended Classifier System (XCS) which is divided into two phases. The first phase is the XCS le...