Tag Archives: compressed sensing

Active clustering

Just a note — the paper “Active Clustering: Robust and Efficient Hierarchical Clustering using Adaptively Selected Similarities,” by Eriksson, Dasarathy, Singh, and Nowak, describing the algorithm which I (but not they) refer to as “compressed clustering,” is now on the arXiv.


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How to find a syphilitic with the Lambert W-function and Fibonacci numbers

I said a few vague words on the All Things Considered piece about the Dorfman protocol for syphilis screening, which is an early example of the exploitation of sparsity to improve signal detection.  Jeffrey Shallit follows up with a really nice explanation of the method at his blog.  Good stuff in the comments, too, especially this souped-up recursive Dorfman suggested by Gareth McCaughan, in which Fibonacci numbers arise in a mysterious way!

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Robert Siegel said my name

I was on All Things Considered today, talking a bit about compressed sensing. They let me tell the syphillis story that didn’t fit in the Wired article. The radio broadcast has come and gone, but you can still hear it at NPR’s website. Laura Balzano made the audio demo; for more explanation and more cool demos, see her page.

Update: I just listened to the piece.  Sorry for the inaccurate title:  Art Silverman, not Robert Siegel, said my name.

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Compressed sensing in Wired

My new Wired piece, about compressed sensing, is now online. For a more technical but still gentle introduction to the subject, see Terry’s blog post.

Update: Igor at Nuit Blanche has a great post clarifying what kind of imaging problems are, and aren’t, currently susceptible to CS methods.

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