Reviews: From Complexity to Simplicity: Adaptive ES-Active Subspaces for Blackbox Optimization

All reviewers are positive about the paper. The paper addresses the problem of black-box optimization, currently of wide interest especially for reinforcement learning. The authors propose adaptive active subspaces techniques for black-box optimization. While the theoretical results seem currently limited, the experimental comparison is detailed and extensive. The proposed approach is therefore quite promising.