NeurIPS 2020

What is being transferred in transfer learning?

Meta Review

This paper provides experimental results and analyses from multiple perspectives for revealing what enables a successful transfer and which part of the network is responsible for that. Reviewers and AC unanimously agree that this paper is well written, proposes new tools for understanding transfer learning and provides novel and important insights. The rebuttal addresses most of the concerns raised by the reviewers. After rebuttal, a reviewer still concerns about the practical value of the understanding since it does not imply a real technique to promote transfer performance. The paper is recommended for acceptance. Please make sure to incorporate the rebuttal material into the camera-ready version.