5 citations · 7 across the 7 of their papers we have counts for
6 papers · 1 filter
Recruiting Heterogeneous Crowdsource Vehicles for Updating a High-definition Map
Wentao Ye, Yuan Luo, Bo Liu +1
The high-definition map is a cornerstone of autonomous driving. Unlike constructing a costly fleet of mapping vehicles, the crowdsourcing paradigm is a cost-effective way to keep a…
Efficient and Cost-effective Vehicle Recruitment for HD Map Crowdsourcing
Wentao Ye, Yuan Luo, Bo Liu +1
The high-definition (HD) map is a cornerstone of autonomous driving. The crowdsourcing paradigm is a cost-effective way to keep an HD map up-to-date. Current HD map crowdsourcing m…
Mechanism Design for Federated Learning with Non-Monotonic Network Effects
Xiang Li, Bing Luo, Jianwei Huang +1
Mechanism design is pivotal to federated learning (FL) for maximizing social welfare by coordinating self-interested clients. Existing mechanisms, however, often overlook the netwo…
Generative AI as Digital Representatives in Collective Decision-Making: A Game-Theoretical Approach
Kexin Chen, Jianwei Huang, Yuan Luo
Generative Artificial Intelligence (GenAI) enables digital representatives to make decisions on behalf of team members in collaborative tasks, but faces challenges in accurately re…
Social Welfare Maximization for Federated Learning with Network Effects
Xiang Li, Yuan Luo, Bing Luo +1
A proper mechanism design can help federated learning (FL) to achieve good social welfare by coordinating self-interested clients through the learning process. However, existing me…
Dual-Role AoI-based Incentive Mechanism for HD map Crowdsourcing
Wentao Ye, Bo Liu, Yuan Luo +1
A high-quality fresh high-definition (HD) map is vital in enhancing transportation efficiency and safety in autonomous driving. Vehicle-based crowdsourcing offers a promising appro…