We study how to train personalized models for different tasks on devices with limited data in a decentralized setting. We propose “Structured Cooperative Learning (SCooL)”, in which a cooperation graph across devices is generated by a graphical model prior and it automatically coordinates mutual learning between devices. By choosing graphical models enforcing different structures, we can derive a rich class of classical and novel decentralized learning algorithms via standard variational inferen…