The ML research community has long been driven by the need to publish, which results in a stark, sometimes ridiculous bias towards complexity. Remember to ask: "can we do this with k-means and logistic regression?"
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Can we do super-resolution with k-means & logreg? Probably Can we do generative models (structured latent space from which on can sample high-res images) with interpolated patches with k-means & logreg? Probably Pixel-to-actions on Atari games with k-means & logreg? Probably Etc
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Can we do 83% accuracy on CIFAR10 with k-means and logistic regression? Yes (Coates 2011).
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I think we should have a "simple, strong baselines" workshop at major ML conferences. This would help focus ML research on real progress.
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unfortunately publish or perish effects all academics, careers depend on publications not thoughtful science which can takes years without clear progress
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