In this work, we focus on managing scientific environmental data, which are measurement readings collected from wireless sensors. In environmental science applications, raw sensor...
The aim of this paper is to propose a new Kalman Filter Recurrent Neural Network (KFRNN) topology and a recursive Levenberg-Marquardt (L-M) algorithm of its learning capable to est...
We provide an overview of using genetic programming (GP) to model stock returns. Our models employ GP terminals (model decision variables) that are financial factors identified by...
Software transactional memory (STM) is an emerging concurrency control mechanism for shared memory accesses. Early abort is one of the important techniques to improve the executio...
This paper investigates a new learning formulation called dynamic group sparsity. It is a natural extension of the standard sparsity concept in compressive sensing, and is motivat...