2 citations · 4 across the 8 of their papers we have counts for
8 papers
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…
A survey on secure decentralized optimization and learning
Changxin Liu, Nicola Bastianello, Wei Huo +2
Decentralized optimization has become a standard paradigm for solving large-scale decision-making problems and training large machine learning models without centralizing data. How…
Recent Advances in Data-driven Intelligent Control for Wireless Communication: A Comprehensive Survey
Wei Huo, Huiwen Yang, Nachuan Yang +10
The advent of next-generation wireless communication systems heralds an era characterized by high data rates, low latency, massive connectivity, and superior energy efficiency. The…
Federated Cubic Regularized Newton Learning with Sparsification-amplified Differential Privacy
Wei Huo, Changxin Liu, Kemi Ding +2
This paper investigates the use of the cubic-regularized Newton method within a federated learning framework while addressing two major concerns that commonly arise in federated le…
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…
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…
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…
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…