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To elaborate, #DeepLearning has certainly been impactful, but along with it came few powerful voices that silenced everyone else. As a graphical model researcher in 2013 i was told by a powerful researcher that it is revenge of #deepnets now. Hope this pettiness ends
The endless debates of mine vs yours (e.g symbolic vs deep learning) is not productive in any way. if u notice, the diversity in those debate is non existent. Only powerful men can openly debate on Twitter. Everyone else feels threatened and silenced. @InclusionInML
And let us make our review process healthy. If you want to improve @InclusionInML pledge to fight against our broken review system. If your fellow reviewer is flawed and lazy, complain to AC and PC. Don't give up those important fights
And let us stop leaderboard chasing of flawed benchmarks. Don't blindly chase a trend just because it came from a famous lab. Be critical and let us start doing so openly. Be honest. Carry out extensive baseline experiments. Publish negative results
More importantly, go back to fundamentals. Low hanging fruits of #DeepLearning are getting exhausted. You will need creativity + hard work. You will need techniques outside #DeepLearning to make a unique impact. Invest in that learning and focus on long term.
THIS. 100% this. I get so turned off by the tone of these debates.
Not to mention that it's not really an either-or in any case.
So so much yes. As someone who literally was silent on Twitter for awhile because of this toxicity, I cannot agree with you more. Thank you for everything. You are an inspiration.
I hope I can dissent a little. I think one good thing is that the debates are conducted in the open. Even if most participants are effectively voiceless, ignored and looked down on (excepting a kind few) for not being part of the in-group, the chance of participating is not nil.
As stupid as the statistics vs. machine learning debate
It's a general rule in academia that ad-hominem attacks happen when the science can't speak for itself...
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