Designing and Learning Trainable Priors with Non-Cooperative Games

26 Jun 2020Bruno LecouatJean PonceJulien Mairal

We introduce a general framework for designing and learning neural networks whose forward passes can be interpreted as solving convex optimization problems, and whose architectures are derived from an optimization algorithm. We focus on non-cooperative convex games, solved by local agents represented by the nodes of a graph and interacting through regularization functions... (read more)

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