We present a comprehensive treatment of 3D object tracking by posing it as a nonlinear state estimation problem. The measurements are derived using the outputs of shape-encoded fi...
Data mining techniques have become central to many applications. Most of those applications rely on so called supervised learning algorithms, which learn from given examples in th...
This paper proposes an architecture for optimized resource allocation in Infrastructure-as-a-Service (IaaS)-based cloud systems. Current IaaS systems are usually unaware of the ho...
This paper examines high dimensional regression with noise-contaminated input and output data. Goals of such learning problems include optimal prediction with noiseless query poin...
— In this paper we develop a new dual decomposition method for optimizing a sum of convex objective functions corresponding to multiple agents but with coupled constraints. In ou...