In kernel-based regression learning, optimizing each kernel individually is useful when the data density, curvature of regression surfaces (or decision boundaries) or magnitude of...
Frequent-pattern mining has been studied extensively on scalable methods for mining various kinds of patterns including itemsets, sequences, and graphs. However, the bottleneck of...
This work proposes and evaluates a sampling algorithm based on wavelet transforms with Coiflets basis to reduce the data sensed in wireless sensor networks applications. The Coiï...
We address unsupervised variational segmentation ofmulti-look complex polarimetric images using a Wishart observation model via level sets. The methods consists of minimizing a fu...
In this paper, a novel method for reducing the runtime complexity of a support vector machine classifier is presented. The new training algorithm is fast and simple. This is achiev...