14 citations · 15 across the 14 of their papers we have counts for
6 papers · 1 filter
Wait-Less Offline Tuning and Re-solving for Online Decision Making
Jingruo Sun, Wenzhi Gao, Ellen Vitercik +1
Online linear programming (OLP) has found broad applications in revenue management and resource allocation. State-of-the-art OLP algorithms achieve low regret by repeatedly solving…
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…
Orientation Determination of Cryo-EM Images Using Block Stochastic Riemannian Subgradient Methods
Wanyu Zhang, Ruili Gou, Huikang Liu +2
The determination of molecular orientations is crucial for the three-dimensional reconstruction of Cryo-EM images. Traditionally addressed using the common-line method, this challe…
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…
Online Linear Programming with Batching
Haoran Xu, Peter W. Glynn, Yinyu Ye
We study Online Linear Programming (OLP) with batching. The planning horizon is cut into batches, and decisions on orders can be delayed to the end of their associated batch. T…
Adam-mini: Use Fewer Learning Rates To Gain More
Yushun Zhang, Congliang Chen, Ziniu Li +6
We propose Adam-mini, an optimizer that achieves on par or better performance than AdamW with 50% less memory footprint. Adam-mini reduces memory by cutting down the learning rate…