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Paper: Deep and Ensemble Learning to Win the Army RCO AI Signal Classification Challenge #473
Typo: datset - dataset
It is not a scientific way of arguing, and it is not supported by any observable or experimented evidence. Please revise this sentence in your conclusion.
2/ "This paper also showed an innovative method of merging different neural networks that were trained with significantly different data. "
I am not sure if it is novel as feature-fusion and multi-view learning exist for a while now in machine learning and deep learning. Authors should check these two research areas and see if necessary references should be included.
The wording could perhaps be improved; it's true that such a claim is unsubstantiated, with no evidence in the paper to justify it. Still, I do appreciate having the authors' best judgment and candor to help us interpret the results. It's worse to leave the false impression that the authors are claiming that those particular architectures are somehow crucial or vitally important, and so I'd favor finding some way to continue to express this opinion in the text.
referenced this pull request
Jun 10, 2019
Our latest PR doesn't address the comments yet.
We will rephrase the first comment and leave the information in the paper. Thanks for all the comments about it.
We will address the second comment by making it more specific to the actual method used to fuse the classifiers. We do not intend claim to be the first to merge classifiers.
@deniederhut For the poster (and other materials) should I assume there will be PDFs of these papers hosted at http://conference.scipy.org/proceedings/scipy2019/ by the time of the conference?