6 citations · 16 across the 11 of their papers we have counts for
11 papers · 1 filter
On the Complexity of BFGS Method for Smooth Convex Optimization
Lijun Ding, Jinwen Yang, Baoyu Zhou
We study the BFGS method with an Armijo-Wolfe line search for minimizing convex functions with Lipschitz-continuous gradients, without assuming strong convexity. We establish a glo…
Optimal Two-Step Stepsize Schedule for Stochastic Gradient Methods
Luwei Bai, Baoyu Zhou
Structured nonconstant large stepsizes can improve the convergence of gradient descent in the deterministic setting. However, in stochastic optimization, aggressive stepsizes can a…
Generalization of Silver Stepsize Schedule to Stochastic Optimization
Luwei Bai, Yang Zeng, Baoyu Zhou
This work introduces a two-step stepsize schedule for stochastic gradient methods minimizing smooth strongly convex functions. We consider the setting where only stochastic gradien…
Optimistic Noise-Aware Sequential Quadratic Programming for Equality Constrained Optimization with Rank-Deficient Jacobians
Albert S. Berahas, Jiahao Shi, Baoyu Zhou
We propose and analyze a sequential quadratic programming algorithm for minimizing a noisy nonlinear smooth function subject to noisy nonlinear smooth equality constraints. The alg…
Sequential Quadratic Optimization for Solving Expectation Equality Constrained Stochastic Optimization Problems
Haoming Shen, Yang Zeng, Baoyu Zhou
A sequential quadratic programming method is designed for solving general smooth nonlinear stochastic optimization problems subject to expectation equality constraints. We consider…
On the Convergence of L-shaped Algorithms for Two-Stage Stochastic Programming
John R. Birge, Haihao Lu, Baoyu Zhou
In this paper, we design, analyze, and implement a variant of the two-loop L-shaped algorithms for solving two-stage stochastic programming problems that arise from important appli…