With the explosive development of the computer vision technology, more and more vision-
based inspection methods enabled by unmanned aerial vehicle technologies have been …

Federated learning (FL) has become one of the mainstream paradigms for multi-party
collaborative learning with privacy protection. As it is difficult to guarantee all FL devices to …

A stagewise decomposition algorithm called “value function gradient learning”(VFGL) is
proposed for large-scale multistage stochastic convex programs. VFGL finds the parameter …

We develop a globally convergent algorithm based on the LP-Newton method, which has
been recently proposed for solving constrained equations, possibly nonsmooth and possibly …

The stabilized version of the sequential quadratic programming algorithm (sSQP) had been
developed in order to achieve fast convergence despite possible degeneracy of constraints …

In this paper an inverse optimal control problem in the form of a mathematical program with
complementarity constraints (MPCC) is considered and numerical experiences are …

It has been previously demonstrated that in the case when a Lagrange multiplier associated
to a given solution is not unique, Newton iterations [eg, those of sequential quadratic …

We consider a class of Newton-type methods that are designed for the difficult case when
solutions need not be isolated, and the equation mapping need not be differentiable at the …

We address the problem of solving a continuously differentiable nonlinear system of
equations under the condition of calmness. This property, also called upper Lipschitz …

We prove a new local upper Lipschitz stability result and the associated local error bound for
solutions of parametric Karush–Kuhn–Tucker systems corresponding to variational …