NeurIPS 2019
Sun Dec 8th through Sat the 14th, 2019 at Vancouver Convention Center
Paper ID:3507
Title:Semi-supervisedly Co-embedding Attributed Networks

The paper tackles the problem of embedding partially labelled attributed networks. It proposes a semi-supervised co-embedding model for attributed networks by generalising the SVAE framework to deal with heterogeneous data. All three reviewers agree that the paper is well written, the methodology is novel and would make a good NeurIPS paper. The empirical evaluation was considered sufficient. The author's rebuttal was very clear and addressed most of the reviewers' concerns.