User Pairing

User pairing, the process of optimally grouping users in a system, is a crucial optimization problem across diverse fields, aiming to maximize efficiency and minimize interference. Current research focuses on developing efficient algorithms, including graph neural networks and reinforcement learning, to solve this problem in contexts ranging from wireless communication networks to federated learning and protein interaction prediction. These advancements improve resource allocation, training speed, and prediction accuracy in various applications, demonstrating the broad impact of effective user pairing strategies.