We study the use of kernel subspace methods for learning low-dimensional representations for classification. We propose a kernel pooled local discriminant subspace method and com...
In this work, we investigate the use of online or “crawling” algorithms to sample large social networks in order to determine the most influential or important individuals wit...
In knowledge discovery applications, where new features are to be added, an acquisition policy can help select the features to be acquired based on their relevance and the cost of...
Clustering is an essential data mining task with various types of applications. Traditional clustering algorithms are based on a vector space model representation. A relational dat...
Caching techniques can be used to reduce bandwidth consumption and data access delay in wireless ad hoc networks. When cache is used, the issue of cache consistency must be addres...