This paper proposes a framework for agent-based distributed machine learning and data mining based on (i) the exchange of meta-level descriptions of individual learning processes ...
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 ...
We introduce a parametric version (pDRUR) of the recently proposed Dimensionality Reduction by Unsupervised Regression algorithm. pDRUR alternately minimizes reconstruction error ...
Fast and accurate fault detection is becoming an essential component of management software for mission critical systems. A good fault detector makes possible to initiate repair a...
We propose a novel algorithm for segmenting multiple motions of different types from point correspondences in multiple affine or perspective views. Since point trajectories associ...