Support vector machines utilizing the 1-norm, typically set up as linear programs (Mangasarian, 2000; Bradley and Mangasarian, 1998), are formulated here as a completely unconstra...
The rise of convex programming has changed the face of many research fields in recent years, machine learning being one of the ones that benefitted the most. A very recent develop...
Soft-error induced reliability problems have become a major challenge in designing new generation microprocessors. Due to the on-chip caches' dominant share in die area and tr...
We model ferromagnetic effects by using reduced scalar potential. An overlapping domain-decomposition technique is proposed to solve the underlying problem in unbounded domain. I...
We adopt the decision-theoretic principle of expected utility maximization as a paradigm for designing autonomous rational agents, and present a framework that uses this paradigm t...