raised by multiple reviewers and next respond to individual questions

We thank all the reviewers for their feedback and pointers to relevant papers. This includes (Kendall et al., 2018), where they learn Kendall et al. 2018), we consider different loss functions on the same output space. There are specific reasons we did not use several multi-task learning algorithms mentioned by REV4 as baselines. Kendall et al. (2018) assumes that all base losses are applications of the same function (max likelihood in this case) We don't see how this method can be extended to our scenario where base losses do not necessarily Moreover, our regularization admits a very different nature. However, directly normalizing the base losses was sufficient for our experiments.