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Near-Optimal Performance of Stochastic Model Predictive Control
This article presents a dynamic regret analysis for stochastic model predictive control (SMPC) in linear systems with quadratic …
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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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Panda: partially approximate newton methods for distributed minimax optimization with unbalanced dimensions
Unbalanced dimensions are crucial characteristics in various minimax optimization problems, such as few-shot learning and …
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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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Inequality Constrained Stochastic Nonlinear Optimization via Active-Set Sequential Quadratic Programming
We study nonlinear optimization problems with a stochastic objective and deterministic equality and inequality constraints, which …
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Superconvergence of Online Optimization for Model Predictive Control
We develop a one-Newton-step-per-horizon, online, lag-$L$, model predictive control (MPC) algorithm for solving discrete-time, …
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