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Online Statistical Inference for Proximal Stochastic Gradient Descent under Markovian Sampling
Nonsmooth stochastic optimization has emerged as a fundamental framework for modeling complex machine learning problems, particularly …
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 …
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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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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A Theoretically Sound Sequential Quadratic Programming Algorithm On Riemannian Manifolds
We design a Sequential Quadratic Programming (SQP) algorithm for solving equality-constrained optimization problems on Riemannian …
An Adaptive Stochastic Sequential Quadratic Programming with Differentiable Exact Augmented Lagrangians
We consider solving nonlinear optimization problems with a stochastic objective and deterministic equality constraints. We assume for …
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Global Convergence of Online Optimization for Nonlinear Model Predictive Control
We study a real-time iteration (RTI) scheme for solving online optimization problem appeared in nonlinear optimal control. The proposed …
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