Review for NeurIPS paper: MMA Regularization: Decorrelating Weights of Neural Networks by Maximizing the Minimal Angles

Weaknesses: The regularization coefficient is important. It can be seen from Figure 3 that the influences of different coefficients are unstable in a single experiment. To better clarify the influences, the author should report the average results of multiple experiments under the same setting. I wonder if the convergence speed and stability are changed after introducing the MMA regularization in the training process. Therefore, it would be better to give the training loss curves with and without MMA regularization.