Reviews: Optimal Decision Tree with Noisy Outcomes

Neural Information Processing Systems 

The setup is original and I see high value in the persistent-noise assumption worked out by the authors. I do have one main question to the authors and while I recommend this paper to be accepted based on significance and appearance of correctness, I do expect a very strong answer on this point for the score to remain high after rebuttal phase. The authors state in their experiment: "To ensure every pair of chemicals can be distinguished, we removed the chemicals that are not identifiable from each other." Well, for significance of the present work, we also need to know how the algorithms are going to behave in the worst-case if there are symmetries and this kind of preprocessing step is omitted. Note that the user would be happy with being presented a set of hypotheses and a certificate that no further test is available to distinguish among them.