Generalized Uniformly Optimal Methods for Nonlinear Programming
Generalized Uniformly Optimal Methods for Nonlinear Programming is a scholarly work, published in 2019 in ''Journal of Scientific Computing''. The main subjects of the publication include nonlinear system, smooth function, regular polygon, convexity, mathematical optimization, compressed sensing, machine learning, convex function, optimization problem, nonlinear programming, mathematics, and convex optimization. The authors present a generic framework to extend such existing algorithms to solve more general nonlinear, possibly nonconvex, optimization problems.