activity
20222025
most citedIntelligent Agents for Auction-based Federated Learning: A Survey

3 citations · 9 across the 7 of their papers we have counts for

collaborators

7 papers

cs.GT2025

A Renegotiable contract-theoretic incentive mechanism for Federated learning

Xavier Tan, Xiaoli Tang, Han Yu

Federated learning (FL) has gained prominence due to heightened concerns over data privacy. Privacy restrictions limit the visibility for data consumers (DCs) to accurately assess…

cs.LG2024★ 2 cited

Agent-oriented Joint Decision Support for Data Owners in Auction-based Federated Learning

Xiaoli Tang, Han Yu, Xiaoxiao Li

Auction-based Federated Learning (AFL) has attracted extensive research interest due to its ability to motivate data owners (DOs) to join FL through economic means. While many exis…

cs.LG2024★ 3 cited

Intelligent Agents for Auction-based Federated Learning: A Survey

Xiaoli Tang, Han Yu, Xiaoxiao Li +1

Auction-based federated learning (AFL) is an important emerging category of FL incentive mechanism design, due to its ability to fairly and efficiently motivate high-quality data o…

cs.AI2023★ 2 cited

Multi-Session Budget Optimization for Forward Auction-based Federated Learning

Xiaoli Tang, Han Yu

Auction-based Federated Learning (AFL) has emerged as an important research field in recent years. The prevailing strategies for FL model users (MUs) assume that the entire team of…

cs.LG2023

Hierarchical Federated Learning Incentivization for Gas Usage Estimation

Has Sun, Xiaoli Tang, Chengyi Yang +5

Accurately estimating gas usage is essential for the efficient functioning of gas distribution networks and saving operational costs. Traditional methods rely on centralized data p…

cs.LG2023★ 1 cited

Utility-Maximizing Bidding Strategy for Data Consumers in Auction-based Federated Learning

Xiaoli Tang, Han Yu

Auction-based Federated Learning (AFL) has attracted extensive research interest due to its ability to motivate data owners to join FL through economic means. Existing works assume…

cs.IR2022★ 1 cited

Towards Trustworthy AI-Empowered Real-Time Bidding for Online Advertisement Auctioning

Xiaoli Tang, Han Yu

Artificial intelligence-empowred Real-Time Bidding (AIRTB) is regarded as one of the most enabling technologies for online advertising. It has attracted significant research attent…