Math.OC

Statistical Inference of Constrained Model Estimation via Derivative-Free Stochastic Sequential Quadratic Programming
We propose a derivative-free stochastic sequential quadratic programming (DF-SSQP) method for solving nonlinear equality-constrained …
Online Statistical Inference of Constrained Stochastic Optimization via Random Scaling
Constrained stochastic nonlinear optimization problems have attracted significant attention for their ability to model complex …
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Online Covariance Estimation in Nonsmooth Stochastic Approximation
We consider applying stochastic approximation (SA) methods to solve nonsmooth variational inclusion problems. Existing studies have …
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Statistical Inference of Constrained Stochastic Optimization via Sketched Sequential Quadratic Programming
We consider online statistical inference of constrained stochastic nonlinear optimization problems. We apply the Stochastic Sequential …
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Trust-Region Sequential Quadratic Programming for Stochastic Optimization with Random Models
In this work, we consider solving optimization problems with a stochastic objective and deterministic equality constraints. We propose …
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Parallel Sequential Quadratic Programming with Overlapping Graph Decomposition and Exact Augmented Lagrangian
In this paper, we address the challenge of solving large-scale graph-structured nonlinear programs (gsNLPs) in a scalable manner. …
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Fully Stochastic Trust-Region Sequential Quadratic Programming for Equality-Constrained Optimization Problems
We propose a trust-region stochastic sequential quadratic programming algorithm (TR-StoSQP) to solve nonlinear optimization problems …
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Convergence Analysis of Accelerated Stochastic Gradient Descent under the Growth Condition
We study the convergence of accelerated stochastic gradient descent for strongly convex objectives under the growth condition, which …
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Constrained Optimization via Exact Augmented Lagrangian and Randomized Iterative Sketching
We consider solving equality-constrained nonlinear, nonconvex optimization problems. This class of problems appears widely in a variety …
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A Fast Temporal Decomposition Procedure for Long-horizon Nonlinear Dynamic Programming
We propose a fast temporal decomposition procedure for solving long-horizon nonlinear dynamic programs. The core of the procedure is …
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