Review for NeurIPS paper: Learning to Learn with Feedback and Local Plasticity

Weaknesses: As pointed out before, one major advantage of their method is that during learning no backpropagation is required. The authors rightly mention that the same advantage applies to meta-learning in recurrent neural networks (e.g. Not of all their contributions are novel: 1. "We provide support for the idea that the credit assignment problem itself may be viewed as an optimization problem, amenable to solution via meta-learning." This has been shown many times before, e.g. This also has been shown many times before, e.g.