Dear Editor,
Herein is my response to manuscript ID XXXXX, entitled “ATMSeer: Increasing Transparency and Controllability in Automated Machine Learning” by Qianwen Wang and colleagues to the ACM Conference on Human Factors in Computing Systems.
The authors present an interactive visualization tool that supports machine learning experts in analyzing the automatic results and in refining the search space of AutoML. This research is well-suited for the remit of the conference.
General speaking, the hypothesis of Automatic Machine Learning is meaningful and foresight. The application of AutoML is beneficial for the workers at the Machine Learning field. It is helpful for the experts in the relevant field using less time, less effort than before to find a high-performance algorithm for their works. 
I recommend weak accept, pending Case Study, Expert Interview, and User Study.
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Congratulations to the authors on a great piece of work, and I look forward to seeing their research.
Sincerely,
Tian Wang