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Overlapping Schwarz Scheme for Linear-Quadratic Programs in Continuous Time
We present an optimize-then-discretize framework for solving linear-quadratic optimal control problems (OCP) governed by …
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Multiple-Shooting Interior-Point Differential Dynamic Programming for Constrained Nonlinear Optimal Control
We propose Multiple-Shooting Interior-Point Differential Dynamic Programming (MS-IPDDP) for finite-horizon constrained nonlinear …
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Inference of Online Newton Methods with Nesterov's Accelerated Sketching
Reliable decision-making with streaming data requires principled uncertainty quantification of online methods. While first-order …
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Derivative-Free Sequential Quadratic Programming for Equality-Constrained Stochastic Optimization
We consider solving nonlinear optimization problems with a stochastic objective and deterministic equality constraints, assuming that …
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High Probability Complexity Bounds of Trust-Region Stochastic Sequential Quadratic Programming with Heavy-Tailed Noise
In this paper, we consider nonlinear optimization problems with a stochastic objective and deterministic equality constraints. We …
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Online Covariance Matrix Estimation in Sketched Newton Methods
Given the ubiquity of streaming data, online algorithms have been widely used for parameter estimation, with second-order methods …
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Near-Optimal Performance of Stochastic Model Predictive Control
This article presents a regret analysis for stochastic model predictive control (SMPC) in linear systems with quadratic performance …
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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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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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