Qing-Guo Lu

Privacy-Preserving Distributed Online Learning With Zeroth-Order Feedback Over Directed Networks

This paper investigates a zeroth-order online optimization problem over a directed network, where each node can only access the function value of its local loss after receiving the decision variable, and information exchange among nodes may incur potential privacy leakage risks. To address these challenges, we propose...