A class of trust-region methods is presented for solving unconstrained nonlinear and possibly nonconvex discretized optimization problems, like those arising in systems governed by...
Serge Gratton, Annick Sartenaer, Philippe L. Toint
Abstract. Support Vector Machines (SVMs) are well-established Machine Learning (ML) algorithms. They rely on the fact that i) linear learning can be formalized as a well-posed opti...
We present a de novo hierarchical simulation framework for first-principles based predictive simulations of materials and their validation on high-end parallel supercomputers and ...
Aiichiro Nakano, Rajiv K. Kalia, Ken-ichi Nomura, ...
In this study, we introduce two improved assessment metrics of multiobjective optimizers, Nondominated Ratio and Spacing Distribution, and analyze their rationality and validity. ...
Maoguo Gong, Licheng Jiao, Haifeng Du, Ronghua Sha...
The concept of artificial evolution has been applied to numerous real world applications in different domains. In this paper, we use this concept in the domain of virology to ev...
Sadia Noreen, Shafaq Murtaza, M. Zubair Shafiq, Mu...