Nearest neighbour classifiers and related kernel methods often perform poorly in high dimensional problems because it is infeasible to include enough training samples to cover the...
Distributed scheduling algorithms for wireless ad hoc networks have received substantial attention over the last decade. The complexity levels of these algorithms span a wide spec...
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 ...
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...
Histograms are used to summarize the contents of relations into a number of buckets for the estimation of query result sizes. Several techniques (e.g., MaxDiff and V-Optimal) have ...
Francesco Buccafurri, Gianluca Lax, Domenico SaccÃ...