Review for NeurIPS paper: Parametric Instance Classification for Unsupervised Visual Feature learning

The authors must be more clear in the introduction that the proposed solution is a "fix" of [12], rather than a new PIC approach, as introduced in lines 29-30 by saying: "... This paper presents a framework which solves instance discrimination by direct parametric instance classification (PIC)". This framework has been already proposed by [12] and the authors must mention it. My understanding is that with the sliding-window sampler, an instance is repeatedly visited several (something like B/S) times in a row, and then not visited for a very long time (something like B * N / S). This means that in the expectation, a single instance class is visited as often as it would have been visited with epoch-based training.