- an acceleration of work around AMP solvers from sparse recovery into matrix factorization.
- the move towards more complex signal structures (we are moving beyond simply cardinality and power laws and it's a about time)
- personally a somewhat better understanding of the analysis based approach
- a continuing slew of good solvers (BSBL, any of the AMP solvers)
- more implementation in C++/Python for reconstruction solvers
- The actual use of several places where people exchange views (LinkedIn also here, Google+ and Reddit).
- a few low level interesting hardware development, ghost imaging being one of them but also the potential replacement of the Anger logic, FREAK
- a few new results that render TV-minimization and NMF a more stable theoretical grounding
- a few promising approach such the QTT tensor factorization, manifold signal processing, Protein-DNA interaction.
- a surge in phase retrieval, blind deconvolution approaches
- a surge of code implementations made available by the researchers themselves (36 in the last three months), two or three are on Github. Our field is becoming a trailblazer when it comes to reproducible research.
- the birth of the RandNLA movement
- some continuing thoughts on post publication peer review process
- a series of compelling videos from GenomeTV
- a series of themes: Predicting the future, accidental cameras, Sunday Morning Insights, some Monthly Reviews
- Curiosity landing on Mars
Image Credit: NASA/JPL/Space Science Institute
N00199979.jpg was taken on December 30, 2012 and received on Earth December 31, 2012. The camera was pointing toward SATURN-ERING at approximately 1,048,438 miles (1,687,298 kilometers) away, and the image was taken using the CL1 and CL2 filters.
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.
2 comments:
Thanks for the blog!
I enjoyed reading it all year round and look forward to next year!
I too wish to thank you for the blog. It must take an incredible amount of your time and we are better off for it.
Thanks,
Leslie
Post a Comment