4 papers
Machine Learning Model Trading with Verification under Information Asymmetry
Xiang Li, Jianwei Huang, Kai Yang +1
Machine learning (ML) model trading, known for its role in protecting data privacy, faces a major challenge: information asymmetry. This issue can lead to model deception, a proble…
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…
Strategic Prompt Pricing for AIGC Services: A User-Centric Approach
Xiang Li, Bing Luo, Jianwei Huang +1
The rapid growth of AI-generated content (AIGC) services has created an urgent need for effective prompt pricing strategies, yet current approaches overlook users' strategic two-st…
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…