In kernel-based regression learning, optimizing each kernel individually is useful when the data density, curvature of regression surfaces (or decision boundaries) or magnitude of...
— The attainable capacity and integrity of a state-of-the-art broadband multi-carrier communication system is highly sensitive to the accuracy of the information available concer...
- In this paper we analyze the performance, utilization, and power estimation of server systems by both adopting the batch service and adjusting the batch size. In addition to redu...
It is well-known that wavelet transforms provide sparse decompositions over many types of image regions but not over image singularities/edges that manifest themselves along curve...
We have studied two efficient sampling methods, Langevin and Hessian adapted Metropolis Hastings (MH), applied to a parameter estimation problem of the mathematical model (Lorent...