Han Yu

A Black Box Optimization-based Bidding Strategy for Data Consumers in Auction-based Federated Learning

This paper departs from the stepwise MDP paradigm and reformulate AFL bidding as a Black-Box Optimization (BBO) problem, and proposes BBO-AFL (Budget-Efficient BBO for DC in AFL), a Budget-Aware Exploration mechanism that decouples high-frequency market cost signals from low-frequency model utility feedback.