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20232025
most citedA survey on secure decentralized optimization and learning

2 citations · 4 across the 8 of their papers we have counts for

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5 papers · 1 filter

eess.SY2025

Decentralized Optimization with Amplified Privacy via Efficient Communication

Wei Huo, Changxin Liu, Kemi Ding +2

Decentralized optimization is crucial for multi-agent systems, with significant concerns about communication efficiency and privacy. This paper explores the role of efficient commu…

eess.SY2024

Communication-efficient and Differentially-private Distributed Nash Equilibrium Seeking with Linear Convergence

Xiaomeng Chen, Wei Huo, Kemi Ding +2

The distributed computation of a Nash equilibrium (NE) for non-cooperative games is gaining increased attention recently. Due to the nature of distributed systems, privacy and comm…

eess.SY2024

Compression-based Privacy Preservation for Distributed Nash Equilibrium Seeking in Aggregative Games

Wei Huo, Xiaomeng Chen, Kemi Ding +2

This paper explores distributed aggregative games in multi-agent systems. Current methods for finding distributed Nash equilibrium require players to send original messages to thei…

eess.SY2024

Differentially Private Dual Gradient Tracking for Distributed Resource Allocation

Wei Huo, Xiaomeng Chen, Lingying Huang +2

This paper investigates privacy issues in distributed resource allocation over directed networks, where each agent holds a private cost function and optimizes its decision subject…

eess.SY2023★ 1 cited

An Efficient Distributed Nash Equilibrium Seeking with Compressed and Event-triggered Communication

Xiaomeng Chen, Wei Huo, Yuchi Wu +2

Distributed Nash equilibrium (NE) seeking problems for networked games have been widely investigated in recent years. Despite the increasing attention, communication expenditure is…