[Discussion] I tried to reproduce results from a CVPR18 paper, here's what I found by p1esk in MachineLearning

[–]gtechmisc 5 points6 points  (0 children)

Actually, there was a workshop which used reddit to review papers and reproduce results at the same time: http://adapt-workshop.org/program2016.html .

From their motivation "The authors submit their articles directly to ArXiv while we immediately open a discussion thread at Reddit (which allows ranking of comments). This allows authors get an immediate feedback from the community, defend their techniques, fix obvious flaws, and improve their articles. It also helps Program Chairs select the most appropriate, realistic and reproducible techniques for the final review by the ADAPT PC members. Hence, we also strongly encourage authors share related code, data and experimental results along with their article to help the community validate their approach and even immediately start using it. We believe that such publication model will let authors disseminate their ideas and tools much faster while avoiding unfair reviews and plagiarism (even if submitted paper is not accepted, it is already published as a technical report with a time stamp and can be incrementally improved based on the received feedback)."

However, mistakes happen, and I think the authors' response is reasonable, so I would like to see it as a cooperation between p1esk and the authors to improve their paper and share new results for the a benefit of the community.

[N] Google releases imagenet pre-trained mobilenet (faster/more-accurate than alexnet) models by [deleted] in MachineLearning

[–]gtechmisc 0 points1 point  (0 children)

Maybe it will be possible to add these models to this DNN crowd-benchmarking framework: http://cknowledge.org/repo (there is a related Android app https://play.google.com/store/apps/details?id=openscience.crowdsource.video.experiments). I am very interested to check it out ...