Database optimization has long relied on traditional methods that struggle with the complexities of modern data environments. These methods often fail to efficiently handle large-scale data, complex ...

In this paper we test different conjugate gradient (CG) methods for solving largescale unconstrained optimization problems. The methods are divided in two groups: the first group includes five basic ...

Machine learning (ML) and deep learning (DL) as two well-known methods of artificial intelligence (AI) have emerged as powerful tools in extracting insights and patterns from vast amounts of data. In ...

Journal of Computational Mathematics, Vol. 26, No. 2 (March 2008), pp. 227-239 (13 pages) We discuss semiconvergence of the extrapolated iterative methods for solving singular linear systems. We ...

This course discusses basic convex analysis (convex sets, functions, and optimization problems), optimization theory (linear, quadratic, semidefinite, and geometric programming; optimality conditions ...

The wide-speed-range vehicles have attracted significant attention due to the exceptional performance in autonomous aerospace ...

In this talk today we will discuss how to improve the resolution of your current CE-SDS methods. We will cover how CE-SDS works and what types of derivatisation for laser induced fluorescence (LIF) ...