The main theme of this paper is to develop a novel eigenvalue optimization framework for learning a Mahalanobis metric. Within this context, we introduce a novel metric learning a...
—The Support Vector Machine is a widely employed machine learning model due to its repeatedly demonstrated superior generalization performance. The Sequential Minimal Optimizatio...
Christopher Sentelle, Michael Georgiopoulos, Georg...
Electromagnetism-like algorithm (EM) is a population-based meta-heuristic which has been proposed to solve continuous problems effectively. In this paper, we present a new meta-h...
Routing FPGAs is a challenging problem because of the relative scarcity of routing resources, both wires and connection points. This can lead either to slow implementations caused...
This paper examines the problem of estimating linear time-invariant state-space system models. In particular it addresses the parametrization and numerical robustness concerns tha...