When clustering a dataset, the right number k of clusters to use is often not obvious, and choosing k automatically is a hard algorithmic problem. In this paper we present an impr...
Objects vary in their visual complexity, yet existing discovery methods perform “batch” clustering, paying equal attention to all instances simultaneously—regardless of the ...
This book covers the following topics: The biological paradigm, Threshold logic, Weighted Networks, The Perceptron, Perceptron learning, Unsupervised learning and clustering algori...
Abstract. In this paper we present a framework for the automatic identification and selection of convex MIMO instruction-set extensions for reconfigurable architecture. The framewo...
Background: The DNA microarray technology allows the measurement of expression levels of thousands of genes under tens/hundreds of different conditions. In microarray data, genes ...
Kin-On Cheng, Ngai-Fong Law, Wan-Chi Siu, Alan Wee...