1 code implementation • 15 Feb 2024 • Ali AhmadiTeshnizi, Wenzhi Gao, Madeleine Udell
Optimization problems are pervasive in sectors from manufacturing and distribution to healthcare.
no code implementations • 11 Feb 2024 • Wenzhi Gao, Chunlin Sun, Chenyu Xue, Dongdong Ge, Yinyu Ye
Online linear programming plays an important role in both revenue management and resource allocation, and recent research has focused on developing efficient first-order online learning algorithms.
no code implementations • 25 Jan 2024 • Wenzhi Gao, Qi Deng
This paper considers stochastic weakly convex optimization without the standard Lipschitz continuity assumption.
1 code implementation • 9 Oct 2023 • Ali AhmadiTeshnizi, Wenzhi Gao, Madeleine Udell
Optimization problems are pervasive across various sectors, from manufacturing and distribution to healthcare.
no code implementations • 21 May 2023 • Yanguang Chen, Wenzhi Gao, Dongdong Ge, Yinyu Ye
We propose a new method to accelerate online Mixed Integer Optimization with Pre-trained machine learning models (PreMIO).
1 code implementation • 2 Sep 2022 • Zhaonan Qu, Wenzhi Gao, Oliver Hinder, Yinyu Ye, Zhengyuan Zhou
Moreover, our implementation of customized solvers, combined with a random row/column sampling step, can find near-optimal diagonal preconditioners for matrices up to size 200, 000 in reasonable time, demonstrating their practical appeal.
no code implementations • NeurIPS 2021 • Qi Deng, Wenzhi Gao
Second, motivated by the success of momentum stochastic gradient descent, we propose a new stochastic extrapolated model-based method, greatly extending the classic Polyak momentum technique to a wider class of stochastic algorithms for weakly convex optimization.