Here is a sample of questions and some answers that appeared on the compressive sensing and matrix factorization groups on LinkedIn.

- John asks a question about the mathematical dual of the SVD he also pointed our attention on Butterfly Decompositions for Arbitrary Unitary Matrices
- German asked a question Regarding rank constraints in principal components pursuit

Recently on the Compressive Sensing Study Group ( 2,904 members )

- Matthieu asked about large scale computations of L1 minimization
- Rohit asked about the Computational complexity of reconstruction (which I think is for hardware)Patrick wonders about IST and AMP phase transitions
- Mrinal wonders about the the value of the constant in compressed sensing?
- Aleksandar wonders about a good implementation of the K-SVD algorithm in C/C++ for windows or clean portable...
- Zhijin wonders about a problem about the difference between CS and low-rank matrix completion
- Matija wonders about what the Powerful CS application fields are..
- WanChien wonders about Non-negative Sparse Recovery
- I wondered if Compressive Holography (was) really **that** compressive ?
- Mihai-Alexandru wondered about Maximum-entropy (recovery) method versus Compressive Sensing
- Misha wondered about if Anyone knew of a (hopefully good) reference for doing compressed sensing type reconstruction with an unknown sensing matrix?
- but to me the most interesting question is by Xuyang: Since dictionary learning is a sparse representation, is it proper to used in one-pixel imaging as a dictionary during the reconstruction?

This image was taken by Rear Hazcam: Right B (RHAZ_RIGHT_B) onboard NASA's Mars rover Curiosity on Sol 635 (2014-05-20 14:52:29 UTC).

Image Credit: NASA/JPL-Caltech

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Image Credit: NASA/JPL-Caltech

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Liked this entry ? subscribe to Nuit Blanche's feed, there's more where that came from. You can also subscribe to Nuit Blanche by Email, explore the Big Picture in Compressive Sensing or the Matrix Factorization Jungle and join the conversations on compressive sensing, advanced matrix factorization and calibration issues on Linkedin.

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