Troubling trends in machine learning scholarship (2018)

Re:Troubling trends in machine learning scholarship (2018) by deepnotderp on Sunday December 01, 2019 @09:17PM (#21679364)

I'm somewhat familiar with compressed sensing, but I only glanced through the linked paper for like a minute, but it looks like you're right. They seem to be taking the overlapped returns and doing some sort of weird sparse basis deconvolution.

Specifically "Using compressed sensing, we analyzed a simulated image with 100 molecules randomly distributed in a 4 µm × 4 µm region (Fig. 1a). Although the images of individual molecules completely overlapped, we could identify almost all of the molecules. "

Unless that is a close enough approximation to a random projection? I'm not that familiar with STORM.

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Re:Troubling trends in machine learning scholarship (2018) by ramraj07 on Sunday December 01, 2019 @10:38PM (#21679629)

My understanding is that you need to apply masks at the sampling stage, and there are legitimate researchers trying to play with that concept using single pixel cameras. Never heard of anyone else try compressed sensing with regular CCD or CMOS sensor array cameras.

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Re:Troubling trends in machine learning scholarship (2018) by deepnotderp on Monday December 02, 2019 @12:12AM (#21679974)

Yeah exactly. I'm not familiar enough with STORM to say if it already provides something close enough to a random projection simply by the acquisition process.

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