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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 …
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 …