After the year in review [17, 38], we had a list of implementations [18-26], a set of meetings [27-30], some hardware implementations [31-33], some meeting videos and papers [34-35], a job [36], some blog etiquette [37] as well as miscellaneous entries [38-41].

We also got a sense as to when compressive imaging might be an advantage over simpler systems [3] but the study did not take into account the technology. When CMOS doesn't work, you're back to square one.

We had a few entries featuring improvement over "older" technology (MRI [7]). One of the surprising finding this past month was the fact that some deterministic approaches seem to be doing as well as random multiplexings [16]. This and the finding with metamaterials [33] might change computational imaging altogether. The whole investigation could use blind deconvolution [4] for random systems. Among the implementations that were made available [18-26] we had a system that mixes matrix factorization and random forest [15] and was the winner of the KDDCup two years in a row [23], an analog sparse recovery solver [22], and a parallel algorithm for solving linear equations that really seems to be O(n^3) unless you have O(n) cores (Thanks Danny) in which cases it becomes O(n^2)..

Adaptive sensing also called Linear Bandits [6] in this recommender systems approach showed up on the radar screen. Randomization brought us some new results in large scale function evaluation [10, 12] and potentially some faster belief propagation (AMP) algorithms [15]. Some conversation on bad reconstruction and error metrics [8, 11, 12] and low rank approaches in the tensor domain [5] provided some depth to the field. It's not just about vectors or sparsity.

Finally, we had two long entries of papers [1,2] and some entries relevant our continuous exploration [9] . A new approach to using compressive sensing outside of the generally well known fields [14], I like it very much! What will February bring ?

The previous Nuit Blanche reviews can be found here.

References:

- This (Past) Month in Compressive Sensing and Matrix Factorization
- Part Deux: This (Past) Month in Compressive Sensing and Matrix Factorization
- When Does Computational Imaging Improve Performance?
- Phase Diagram and Approximate Message Passing for Blind Calibration and Dictionary Learning
- Tensor completion based on nuclear norm minimization for 5D seismic data reconstruction
- Linear Bandits in High Dimension and Recommendation Systems
- Spread spectrum compressed sensing MRI using chirp radio frequency pulses
- Signal reconstruction in linear mixing systems with additive error metrics (video introduction)
- Around the blogs in 80 summer hours
- Fast Food: Approximating Kernel Expansion in Loglinear Time
- All hopes may not be crushed all at once
- It's not a bad reconstruction, just the end of an illusion...
- Fast Functions via Randomized Algorithms: Linear Regression with Random Projections
- A Computational model for compressed sensing RNAi cellular screening
- Recent Algorithms Development and Faster Belief Propagation algorithms
- Deterministic matrices matching the compressed sensing phase transitions of Gaussian random matrices
- A gut feeling review of 2012.
- Structure-Based Bayesian Sparse Reconstruction - implementation -
- Improving Dictionary Learning: Multiple Dictionary Updates and Coefficient Reuse - implementation -
- A Randomized Parallel Algorithm with Run Time $O(n^2)$ for Solving an $n \times n$ System of Linear Equations -
- Compressed Sensing with Correlation Between Measurements and Noise - implementation -
- Convergence Speed of a Dynamical System for Sparse Recovery - implementation -
- SVDFeature: A Toolkit for Feature-based Collaborative Filtering - implementation -
- A Probabilistic Approach to Robust Matrix Factorization - implementation -
- Heliometric Stereo: Shape from Sun Position - implementation
- AMP: Assembly Matching Pursuit, Metagenomic units (MGUs) discovery through sequence-based dictionary learning - implementation -
- ROKS 2013 International Workshop on Advances in Regularization, Optimization, Kernel Methods and Support Vector Machines:
- Phased Array 2013 announcement
- SPARS'13 deadlines approaching soon ! #spars13 and #Spars13 announcements and clarifications
- Fête Parisienne in Computation, Inference and Optimization: A Young Researchers' Forum
- Three-dimensional ghost imaging ladar
- Correspondence Diﬀerential Ghost Imaging
- Metamaterial Apertures for Computational Imaging
- The #NIPS2012 Videos are out
- Pacific Symposium on Biocomputing papers
- CSJob: Faculty at University of Wisconsin-Madison
- Welcome back to the Jungle
- Where are we now ?
- Agents of Change
- The Technical Side of the Nuclear Rockets Option
- Sudoku, Compressive Sensing and Thermodynamics

Image Credit: NASA/JPL-Caltech

This image was taken by Navcam: Left A (NAV_LEFT_A) onboard NASA's Mars rover Curiosity on Sol 176 (2013-02-03 00:25:21 UTC) .

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