Not every failed result is worth noting but reporting surprising failures is useful. All these effectively maintain a trace, reducing redundancy & increasing coherence (many studies claim interactions that would be lots harder to support if they could not pretend independence)
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So there are more than a single issue here but I have been discussing this usually on my own and often without any support from others since the academic year of 2009/2010.
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:( It's sad people don't see the importance of the points you've brought up. It's fascinating to see another field facing nearly the same issues as machine learning research and suggesting similar trajectories through them.
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Yup! Not only similar issues, but I think the "root" is the same and the crossover of people/ideas from the two areas is not a coincidence!
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I wanted to say something like, really subfields of the same field distinguished by emphasis placed on biological plausibility but thought that sounded to much like the kind of thing physicists say :p
- End of conversation
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