stat.ML

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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An Asymptotically Optimal Method for Constrained Stochastic Optimization
We perform statistical inference for the solution of stochastic optimization problems with equality and box inequality constraints. The …
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Online Covariance Matrix Estimation in Stochastic Inexact Newton Methods
Online algorithms gain prominence as the volume of data explodes, among which second-order methods are known for their robustness. …
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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Trust-Region Sequential Quadratic Programming for Stochastic Optimization with Random Models
We design a trust-region sequential quadratic programming (TR-SQP) method to find both first- and second-order stationary points for …
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 …
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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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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Statistical Inference of Constrained Stochastic Optimization via Sketched Sequential Quadratic Programming
We consider statistical inference of equality-constrained stochastic nonlinear optimization problems. We develop a fully online …
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