Review for NeurIPS paper: Modeling and Optimization Trade-off in Meta-learning

When trading off between MAML and DRS, the learning rate in MAML provides a simple and explicit mechanism to trade between these two algorithms (ignoring task dataset size). In particular, as the learning rate goes to zero, MAML becomes DRS. Thus, if proper hyperparameter tuning is performed on the learning rate, then I would expect MAML to always out-perform DRS given a reasonable number of samples. In the meta-RL benchmarks, the original MAML paper [1] reports using a learning rate of 0.1 for TRPO-MAML but the largest value evaluated in this work is 0.01. Does that change the performance?