In this paper, we propose a stochastic method for solving equality constrained optimization
problems that utilizes predictive variance reduction. Specifically, we develop a method …

A sequential quadratic optimization algorithm for minimizing an objective function defined by
an expectation subject to nonlinear inequality and equality constraints is proposed …

We consider minimizing a smooth and strongly convex objective function using a stochastic
Newton method. At each iteration, the algorithm is given an oracle access to a stochastic …

We propose a trust-region stochastic sequential quadratic programming algorithm (TR-
StoSQP) to solve nonlinear optimization problems with stochastic objectives and …

A step-search sequential quadratic programming method is proposed for solving nonlinear
equality constrained stochastic optimization problems. It is assumed that constraint function …

We apply a stochastic sequential quadratic programming (StoSQP) algorithm to solve
constrained nonlinear optimization problems, where the objective is stochastic and the …

The primary goal of this paper is to provide an efficient solution algorithm based on the
augmented Lagrangian framework for optimization problems with a stochastic objective …

Nonconvex constrained stochastic optimization has emerged in many important application
areas. Subject to general functional constraints it minimizes the sum of an expectation …

To achieve welding torch trajectory continuous smooth and welding time the shortest, which
of the underwater visual welding robot end, a method of interpolation the location-time …

We introduce adaptive sampling methods for stochastic programs with deterministic
constraints. First, we propose and analyze a variant of the stochastic projected gradient …