We have had quite a few new items, including my first paper published in the realm of compressive sensing since the last Nuit Blanche in Review (June 2014). We also had 11 implementations made available by their respective authors:
- GreBsmo: Greedy Bilateral Sketch, Completion & Smoothing - implementation -
- Adaptive-Rate Compressive Sensing Using Side Information - implementation -
- Tight convex relaxations for sparse matrix factorization - implementation -
- Mondrian Forests: Efficient Online Random Forests - implementation -
- Fast matrix completion without the condition number - implementation -
- Dynamic MR image reconstruction–separation from undersampled (k,t)-space via low-rank plus sparse prior - implementation -
- Understanding Random Forests: From Theory to Practice - implementation -
- Phase Retrieval via Wirtinger Flow: Theory and Algorithms - implementation -
- Randomized Numerical Linear Algebra for Large Scale Data Analysis ( libSkylark: Sketching based Matrix computations for Machine Learning )
- SASIR: LOFAR Sparse Image Reconstruction - implementation -
- Stable, Robust and Super Fast Reconstruction of Tensors Using Multi-Way Projections - implementation -
My paper also resulted in a few blog entries:
- Imaging With Nature: Compressive Imaging Using a Multiply Scattering Medium
- The Post Publication Peer Review of "Imaging With Nature: Compressive Imaging Using a Multiply Scattering Medium"
- Additional Photos and Video to "Imaging With Nature: Compressive Imaging Using a Multiply Scattering Medium"
- Follow up on "Imaging With Nature: Compressive Imaging Using a Multiply Scattering Medium"
I also featured a certain number of related papers
- Speckle suppression via sparse representation for wide-field imaging through turbid media
- Random Matrices Are Too Damn Large !
- Another Comment on " Random Matrices Are Too Damn Large ! "
- Compressed Sensing via Universal Denoising and Approximate Message Passing
- Transmission of quantum entanglement through a random medium / Terahertz compressive imaging with metamaterial spatial light modulators
It also had me to be more focused about certain publishing options. More on that later:
Other papers and notes were also featured:
- Compressed Subspace Matching on the Continuum / Subspace Learning From Bits
- Euclid in a Taxicab: Sparse Blind Deconvolution with Smoothed $\ell_1/ell_2$ Regularization
- Complexity-Matching Universal Signal Estimation in Compressed Sensing
- Tensor Networks for Big Data Analytics and Large-Scale Optimization Problems
- Rows vs Columns for Linear Systems of Equations - Randomized Kaczmarz or Coordinate Descent ?
- Context Aware Recommendation Systems ( Lei Tang, Xavier Amatriain)
- The Gamification Design Problem
- The 200 Million Dollar Assumption
A discussion on Uncertainty Relations with compressive sensing led to a few posts:
- Simultaneous Measurement of Complementary Observables with Compressive Sensing
- Entropic Uncertainty Relations in Quantum Physics / On asymptotic structure in compressed sensing
- Some Comments: Universal Compressed Sensing of Markov Sources, A survey of uncertainty principles and some signal processing applications, Refined support and entropic uncertainty inequalities
I also did a presentation at the Paris Context Aware Meetup:
Sunday Morning Insight:
Meetings (CfP, Slides, Videos)
- GdR ISIS: Acquisition/Echantillonnage comprimé : quelles réalisations/applications pratiques ?
- Saturday Morning Videos: 27th Annual Conference on Learning Theory (COLT), Barcelona 2014
- Last Call for Contributions - TCMM 2014 International Workshop on Technical Computing for Machine Learning and Mathematical Engineering, 8 - 12 September, 2014 - Leuven, Belgium
- Slides: Summer School on Hashing: Theory and Applications, 2014
- Video Stream: GraphLab Conference 2014
- Slides: Science on the Sphere
- It's not as random as it seems, Paris Context Aware Meetup #1
- Saturday Morning Videos: 27th Annual Conference on Learning Theory (COLT), Barcelona
- Saturday Morning Videos: Machine Learning Summer School Pittsburgh 2014, Muthu Muthukrishnan
- Saturday Morning Videos: Paris-Saclay Center for Data Science kick-off meeting
Other Videos
Hamming's time
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