The aim of this paper is to investigate the multiple attribute decision making problems with linguistic information, in which the information about attribute weights is incomplete...
The conventional mean shift algorithm has been known to be sensitive to selecting a bandwidth. We present a robust mean shift algorithm with heterogeneous node weights that come f...
Computer science has served to insulate programs and programmers from knowledge of the underlying mechanisms used to manipulate information, however this fiction is increasingly h...
Neil Gershenfeld, David Dalrymple, Kailiang Chen, ...
This paper presents a codebook learning approach for image classification and retrieval. It corresponds to learning a weighted similarity metric to satisfy that the weighted simil...
We propose and evaluate a family of methods for converting classifier learning algorithms and classification theory into cost-sensitive algorithms and theory. The proposed conve...