Analytical and numerical techniques like gradient descent, genetic algorithm, ... to solve a convex unconstrained nonlinear optimization problem from scratchh without using any python library - khe ...

This paper proposes a quaternion-valued one-layer recurrent neural network approach to resolve constrained convex function optimization problems with quaternion variables. Leveraging the novel ...

We present preliminary analysis for ExtraPush under a bounded sequence assumption. For Normalized ExtraPush, we show that it naturally produces a bounded, linearly convergent sequence provided that ...

Convex Optimization and Feasibility Problems Publication Trend The graph below shows the total number of publications each year in Convex Optimization and Feasibility Problems.

A worst-case complexity analysis in terms of evaluations of the problem's function and derivatives is also presented for the Lipschitz continuous case and for a variant of the resulting algorithm.

Using Particle Swarm Optimizer to Optimize a Non-convex Function Introduction This project focuses on implementing the Particle Swarm Optimization (PSO) algorithm to optimize a non-convex function.

In this paper, we consider the convergence rate of ADMM when applying to the convex optimization problems that the subdifferentials of the underlying functions are piecewise linear multifunctions, ...