This paper proposes a novel application of differential evolution to solve a difficult dynamic optimisation or optimal control problem. The miss distance in a missile-target engag...
In this paper, a supervised neural network training technique based on constrained optimization is developed for preserving prior knowledge of an input
We study a generalized framework for structured sparsity. It extends the well known methods of Lasso and Group Lasso by incorporating additional constraints on the variables as pa...
Luca Baldassarre, Jean Morales, Andreas Argyriou, ...
— A new sub-space max-monomial modeling scheme for CMOS transistors in sub-micron technologies is proposed to improve the modeling accuracy. Major electrical parameters of CMOS...
Regressions has successfully been incorporated into memetic algorithm (MA) to build surrogate models for the objective or constraint landscape of optimization problems. This helps ...
Stephanus Daniel Handoko, Chee Keong Kwoh, Yew-Soo...