8 citations · 18 across the 16 of their papers we have counts for
5 papers · 1 filter
When Does Primal Interior Point Method Beat Primal-dual in Linear Optimization?
Wenzhi Gao, Huikang Liu, Yinyu Ye +1
The primal-dual interior point method (IPM) is widely regarded as the most efficient IPM variant for linear optimization. In this paper, we demonstrate that the improved stability…
Gradient Methods with Online Scaling
Wenzhi Gao, Ya-Chi Chu, Yinyu Ye +1
We introduce a framework to accelerate the convergence of gradient-based methods with online learning. The framework learns to scale the gradient at each iteration through an onlin…
OptiMUS-0.3: Using Large Language Models to Model and Solve Optimization Problems at Scale
Ali AhmadiTeshnizi, Wenzhi Gao, Herman Brunborg +3
Optimization problems are pervasive in sectors from manufacturing and distribution to healthcare. However, most such problems are still solved heuristically by hand rather than opt…
Randomized Nyström Preconditioned Interior Point-Proximal Method of Multipliers
Ya-Chi Chu, Luiz-Rafael Santos, Madeleine Udell
We present a new algorithm for convex separable quadratic programming (QP) called Nys-IP-PMM, a regularized interior-point solver that uses low-rank structure to accelerate solutio…
OptiMUS: Scalable Optimization Modeling with (MI)LP Solvers and Large Language Models
Ali AhmadiTeshnizi, Wenzhi Gao, Madeleine Udell
Optimization problems are pervasive in sectors from manufacturing and distribution to healthcare. However, most such problems are still solved heuristically by hand rather than opt…