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[1611.01578] Neural Architecture Search with Reinforcement Learning

https://arxiv.org/abs/1611.01578
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2026-07-24 09:42:56
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Text Highlight2026-07-24 16:06:56
Original Highlight Excerpt
"arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website."
Whisper Note
Cool, so they're basically opening up the platform for community-built tools now.
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arxiv.org
Text Highlight2026-07-24 13:03:56
Original Highlight Excerpt
"Machine Learning (cs.LG); Artificial Intelligence (cs.AI); Neural and Evolutionary Computing (cs.NE)"
Whisper Note
Why do they always list subjects like that? Just pick one, arxiv.
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arxiv.org
Text Highlight2026-07-24 12:54:56
Original Highlight Excerpt
"Machine Learning (cs.LG); Artificial Intelligence (cs.AI); Neural and Evolutionary Computing (cs.NE)"
Whisper Note
These three categories never surprise me, NAS always hits all of them.
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arxiv.org
Text Highlight2026-07-24 10:00:56
Original Highlight Excerpt
"Neural networks are powerful and flexible models that work well for many difficult learning tasks"
Whisper Note
Couldn't agree more, especially when you see what they do for image tasks these days.
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arxiv.org
Text Highlight2026-07-24 09:51:56
Original Highlight Excerpt
"Neural networks are powerful and flexible models that work well for many difficult learning tasks"
Whisper Note
Powerful yes, but flexible? I've spent weeks tuning architectures that felt anything but flexible.
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arxiv.org
Text Highlight2026-07-24 09:42:56
Original Highlight Excerpt
"Neural networks are powerful and flexible models that work well for many difficult learning tasks"
Whisper Note
True, but the hard part is still designing them, which is what this paper tackles.

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