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[D] Does The Inability Of NAS Algorithms To Outperform Random Search Indicate That Our Algorithms Suck, Or That Random Search Is Surprisingly Effective In Large Spaces?

One of the most counterintuitive developments in ML research is that, despite huge amounts of resources and brain power being poured into field, state-of-the-art neural architecture search algorithms still can’t outperform pure random search.

This fact is so jarring that I’m surprised it’s not being talked about more often.

What exactly does this mean? Are we just putting out ineffective automl algorithms, or has the power of random search been completely overlooked?

submitted by /u/mystikaldanger
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.