NeurIPS 2020

LoCo: Local Contrastive Representation Learning

Meta Review

Reviewers were satisfied by the author's response and clarifications. Discussion phase also contributed to harmonizing their view on the relevance and usefulness of well-working local criteria. As a result, R1 and R5 increased their score. The consensus is that the work is a novel and valuable contribution to research on local un/self-supervised learning criteria, with potential relevance for memory savings and biologically plausible alternatives to backpropagation. The AC agrees and recommends acceptance.