Why There’s No iMessage for Android
June 11, 2021
AMD to roll out Zen 3-based APUs in August
June 11, 2021

[D] Algorithm to detect cheaters in ML conferences

Background: We know that there is at least some cheaters that form one or several collusion rings in ML conferences. The situation is described in this article: https://cacm.acm.org/magazines/2021/6/252840-collusion-rings-threaten-the-integrity-of-computer-science-research/fulltext.

I think some of us may want to find them (by data analysis, of course). I know it's controversy, due to obvious reasons. I assume after the article, the cheaters may feel threatened, and hence reduce their cheating behaviors in several next conferences. They will be brave if they keep doing it now.

My idea is use some analysis algorithms to find the anomaly in their behaviors. Several points I think would be useful: * We can create a collaboration/publishing network of authors that published in ML conferences in recent years * People in the same collusion ring carefully avoid COI, which means they're not in the same institution for several years, no collaboration in papers and proposals in years * Their publications in top ML conferences after 21/6 will be reduced significantly

After building the network and using some assumptions, I think there is some algorithm may help detecting potential cheaters.

What do you think about this? Is it feasible?

submitted by /u/Unhappy_Barracuda_59
[link] [comments]


Comments are closed.