activity
20082026
most citedOn the Linear Convergence of the ADMM in Decentralized Consensus Optimization

873 citations · 5.4k across the 120 of their papers we have counts for

collaborators

121 papers

math.OC2026

Restarted Reflected Halpern Acceleration for Augmented Primal-Dual Methods

Benqi Liu, Ju Cao, Wotao Yin +1

We study linearly constrained composite convex optimization with a smooth term and a proximable nonsmooth term. We develop a unified augmented primal-dual framework with primal-dua…

cs.AI2023★ 2 cited

A Human-on-the-Loop Optimization Autoformalism Approach for Sustainability

Ming Jin, Bilgehan Sel, Fnu Hardeep +1

This paper outlines a natural conversational approach to solving personalized energy-related problems using large language models (LLMs). We focus on customizable optimization prob…

cs.MS2023★ 1 cited

MindOpt Tuner: Boost the Performance of Numerical Software by Automatic Parameter Tuning

Mengyuan Zhang, Wotao Yin, Mengchang Wang +7

Numerical software is usually shipped with built-in hyperparameters. By carefully tuning those hyperparameters, significant performance enhancements can be achieved for specific ap…

cs.LG2023

DSGD-CECA: Decentralized SGD with Communication-Optimal Exact Consensus Algorithm

Lisang Ding, Kexin Jin, Bicheng Ying +2

Decentralized Stochastic Gradient Descent (SGD) is an emerging neural network training approach that enables multiple agents to train a model collaboratively and simultaneously. Ra…

cs.LG2023★ 1 cited

Towards Constituting Mathematical Structures for Learning to Optimize

Jialin Liu, Xiaohan Chen, Zhangyang Wang +2

Learning to Optimize (L2O), a technique that utilizes machine learning to learn an optimization algorithm automatically from data, has gained arising attention in recent years. A g…

cs.LG2023

Lower Bounds and Accelerated Algorithms in Distributed Stochastic Optimization with Communication Compression

Yutong He, Xinmeng Huang, Yiming Chen +2

Communication compression is an essential strategy for alleviating communication overhead by reducing the volume of information exchanged between computing nodes in large-scale dis…