Haoyong Wang

MartDE: A Privacy-Preserving and Cost-Efficient Evaluation Framework for Data Marketplaces

The development of machine learning models increasingly relies on high-quality data that resides in private domains. To enable secure and value-driven data exchange under strict privacy regulations, federated learning (FL) has emerged as a key primitive by enabling the trading of model utilities ins