We present a data-driven approach for target detection and identification based on a linear mixture model. Our aim is to determine the existence of certain targets in a mixture w...
—This paper presents a mathematical framework for resource reservation in TCP/IP networks by invoking a dynamic system viewpoint on the congestion monitoring processes occurring ...
Abstract. The concept of Ensemble Learning has been shown to increase predictive power over single base learners. Given the bias-variancecovariance decomposition, diversity is char...
This paper proposes a novel subspace approach towards direct identification of a residual model for fault detection and isolation (FDI) in a system with non-uniformly sampled mult...
Automated feature discovery is a fundamental problem in machine learning. Although classical feature discovery methods do not guarantee optimal solutions in general, it has been r...