A computationally efficient approach to local learning with kernel methods is presented. The Fast Local Kernel Support Vector Machine (FaLK-SVM) trains a set of local SVMs on redu...
The design of hash functions by means of evolutionary computation is a relatively new and unexplored problem. In this work, we use Genetic Programming (GP) to evolve robust and fa...
Clustering has been one of the most widely studied topics in data mining and k-means clustering has been one of the popular clustering algorithms. K-means requires several passes ...
Equi-depth histograms represent a fundamental synopsis widely used in both database and data stream applications, as they provide the cornerstone of many techniques such as query ...
Blind source separation (BSS) is a process to reconstruct source signals from the mixed signals. The standard BSS methods assume a fixed set of stationary source signals with the ...