3 papers
cs.LG2026
Accelerating Optimization and Machine Learning through Decentralization
Ziqin Chen, Zuang Wang, Yongqiang Wang
Decentralized optimization enables multiple devices to learn a global machine learning model while each individual device only has access to its local dataset. By avoiding the need…
eess.SY2026
Local Updates in Distributed Optimization: Provable Acceleration and Topology Effects
Zuang Wang, Yongqiang Wang
Inspired by the success of performing multiple local optimization steps between communication rounds in federated learning, incorporating such local updates into distributed optimi…
math.OC2025
Guaranteeing Both Consensus and Optimality in Decentralized Nonconvex Optimization with Multiple Local Updates
Jie Liu, Zuang Wang, Yongqiang Wang
Scalable decentralized optimization in large-scale systems hinges on efficient communication. A common way to reduce communication overhead is to perform multiple local updates bet…