Since the last Nuit Blanche in Review, we had quite a few implementations as well as some very interesting meetups/meetings (check the video section).
Implementations
- Enhancing Pure-Pixel Identification Performance via Preconditioning - implementation -
- NLCS : Non-Local Compressive Sampling Recovery - implementation -
- ROSL : Robust Orthonormal Subspace Learning: Efficient Recovery of Corrupted Low-rank Matrices - implementation -
- Multidimensional Compressed Sensing and their Applications - implementation -
- A Riemannian approach to low-rank algebraic Riccati equations - implementation -
- Randomized Comments: Code for GWAS and CS study, a new blog, Geometric theory of information
- The SwAMP Thing! Sparse Estimation with the Swept Approximated Message-Passing Algorithm -implementation -
- NLR-CS : Compressive Sensing via Nonlocal Low-rank Regularization - implementation -
- UnLocBox / PyUnLocBox (Matlab and Python convex optimization toolbox)
- PURIFY: a new algorithmic framework for next-generation radio-interferometric imaging - implementation -
- Matrix-free Interior Point Method for Compressed Sensing Problems / A Second order Method for Compressed Sensing with Coherent and Redundant Dictionaries - implementation -
Some additional thoughts:
- About t'em Random Projections in Random Forests
- Random Branches
- ... There will be a "before" and "after" this paper ...
- Another Friday the 13th news...
- Geodesic Convexity and Covariance Estimation, Medians and means in Riemannian geometry, MaxEnt'14
- Randomized Comments: Compressive Sensing Ten Year Anniversary, A Comment; A Review, Beyond gaussians with AMP, Searching Nuit Blanche with two labels, The Golosino seminar
- Randomized Comments: Code for GWAS and CS study, a new blog, Geometric theory of information
Other papers:
- Distributed Outlier Detection using Compressive Sensing
- Impression Store: Compressive Sensing-based Storage for Big Data Analytics
- Cal-AMP : Blind Sensor Calibration using Approximate Message Passing
- From Denoising to Compressed Sensing
- Takens' Embedding and Riemannian preconditioning
- Non-negative Principal Component Analysis: Message Passing Algorithms and Sharp Asymptotics
- Compressive Imaging Technology
- Unifying Linear Dimensionality Reduction
- Compressed sensing: Variations on a theme
- Compressive Sensing Applications
- Optimal CUR Matrix Decompositions
- Compressive Imaging via Approximate Message Passing with Image Denoising
Meetings
Meetups
Videos:
CfP :
Saturday Morning Videos:
More
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