Review for NeurIPS paper: Trading Personalization for Accuracy: Data Debugging in Collaborative Filtering

The proposed algorithm is limited to matrix factorization model, and can be hardly extended to more state-of-art neural network-based latent factor models proposed in recent years. Because the derivate of model parameters with respect to training labels in Equation (7) needs to be a closed form solution as in matrix factorization. This may restrict a broader impact of the proposed solution. I'm concerned about the authors' claim on the trade-off between personalization and accuracy. As emphasized in the title, the authors consider the performance gain of the proposed algorithm as trading personalization for accuracy, but there is no direct empirical evaluation evidence to support this claim.