Review for NeurIPS paper: Information Theoretic Regret Bounds for Online Nonlinear Control

The introduced algorithm LC3 enjoys an O(sqrt{T}) regret bound against the optimal controller with no explicit dependence on the dimension of the system dynamics. The paper received a mostly positive evaluation from the reviewers with one vote below the acceptance threshold (scores of 7, 7, and 5). The main strengths of the paper were identified as: - Novel results (on of the first in adaptive non-linear control) which should be of interest to the NeurIPS community. Several weaknesses were also pointed out: - One of the reviewers found the contribution of the theoretical results to be marginal comparing to the past work.