NeurIPS 2020

Domain Generalization for Medical Imaging Classification with Linear-Dependency Regularization

Meta Review

Four knowledgeable reviewers have mixed opinions: R1 and R4 -- 'Marginally above the acceptance threshold', R3 -- 'Marginally above the acceptance threshold', and R2 -- 'Reject'. R2, who is the least confident among 4 reviewers, has a main concern about comparing with two works [a] Multi-source Domain Adaptation for Face Recognition and [b] Multi-Source Domain Adaptation: A Causal View. I read the paper and rebuttal and decide to downgrade this concern because the paper is mainly about domain generalization (DG), rather than domain adaptation (DA). There are quite differences between them and hence it is not fully necessary to compare the proposed DG approach with DA approaches thoroughly. Also, the authors agree to cite these works in future version, which to me is fine. R3 points out the only weakness that this paper misses details on reproducing the experiments, such as layer setting, and hyper parameters. The main part of these details is in fact in the supplementary materials; so I decide to ignore this concern. To sum up, the paper is accepted. It is highly recommended that the author can better justify the linear dependency regularization.