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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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Hessian Averaging in Stochastic Newton Methods Achieves Superlinear Convergence
We consider minimizing a smooth and strongly convex objective function using a stochastic Newton method. At each iteration, the …
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On the Convergence of Overlapping Schwarz Decomposition for Nonlinear Optimal Control
We study the convergence properties of an overlapping Schwarz decomposition algorithm for solving nonlinear optimal control problems …
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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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High-dimensional Index Volatility Models via Stein's Identity
We study the estimation of the parametric components of single and multiple index volatility models. Using the first- and second-order …
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Estimating Differential Latent Variable Graphical Models with Applications to Brain Connectivity
Differential graphical models are designed to represent the difference between the conditional dependence structures of two groups, and …
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Exponential Decay in the Sensitivity Analysis of Nonlinear Dynamic Programming
In this paper, we study the sensitivity of discrete-time dynamic programs with nonlinear dynamics and objective to perturbations in the …
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High-dimensional Varying Index Coefficient Models via Stein's Identity
We study the parameter estimation problem for a varying index coefficient model in high dimensions. Unlike the most existing works that …
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