Tuesday, October 04, 2011

Around the blogs in 80 hours, Compressive Sensing Edition

Some surprises this week:

Zhilin: A simple comparison of sparse signal recovery algorithms when the dictionary matrix is highly coherent

Tianyi : Hamming Compressed Sensing-recovering k-bit quantization from 1-bit measurements with linear non-iterative algorithm

Bob: Phase transitions for MP?

Dirk: Second news from ILAS 11

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mirror2image said...

The result for coherent matrices are not surprising IMHO, because best performing methods("Bayesian" T_MSBL etc) are using additional information - which vectors are coherent and factor that into measurement model. The only surprising thing is that Smooth L0 sometimes works. IIRC it's based on something like Cauchy estimator, so it can explain why it more robust than L1.
PS it it possible to turn off captcha? I have difficulty processing it - I'm not a bot )))

Igor said...


I am sorry I am going to put back the capcha as I am getting flooded with spam. Sorry.


Ulugbek said...

From a quick glance to the experiment code I can say that comparison is not exactly fair, so the results are not surprising.

Igor said...


Can you expand on that ?