Rust + WASM sublinear-time solver for asymmetric diagonally dominant systems. Exposes Neumann series, push, and hybrid random-walk algorithms with npm/npx CLI and Flow-Nexus HTTP streaming for swarm ...

Abstract: For the conjugate gradient method to solve the unconstrained optimization problem, given a new interval method to obtain the direction parameters, and a new conjugate gradient algorithm is ...

Abstract: Conjugate gradient techniques are widely used to solve unconstrained optimization issues. The accelerated conjugate gradient approach provides superior numerical effects for the ...

Motivation: sparse LM optimizer relies on a sparse Ax = b solver Hi! We are working on a sparse Levenberg–Marquardt optimizer, and we have already sparsified the Jacobian matrix and A matrix (derived ...

where and for, are random matrices and vectors. When, stochastic generalized linear complementarity problems reduce to the classic Stochastic Linear Complementarity Problems (SLCP), which has been ...

A class of finite step iterative methods, conjugate gradients, for the solution of an operator equation, is presented on this paper to solve electromagnetic scattering. The method of generalized ...

The nonlinear conjugate gradient method is a very useful technique for solving large scale minimization problems and has wide applications in many fields. In this paper, we present a new algorithm of ...