Reviews: Sparse Attentive Backtracking: Temporal Credit Assignment Through Reminding

The authors augment an RNN with skip connections in time, that are sparsely gated by learnable attention. This allows to reap the benefits of full BPTT while effectively using only truncated BPTT. While other forms of attention-gated skip connections in time have been suggested before, to which the authors compare, here the authors looked at sparse (still differentiable) retrieval where only a few top memory entries are selected, enabling the benefits of backpropagating over only a few selected earlier states. Overall, I think this work is very significant, both for enabling faster implementations of BPTT when considering long time horizons, but also for suggesting future directions for how the brain might perform credit assignment and for pointing out further brain strategies / biases to employ in machine learning. With some clarifications / changes as below, I recommend the acceptance of this article for NIPS. 1. In lines 58-60, the authors say that BPTT would require "playing back these events".