What a month it has been since last March! First, we have lost a unique individual (Seth Roberts). We also witnessed the breakout of convnets (here and here), while being made aware of the intricacies of decyphering Dolphin communications. The Sunday Morning Insight entry entitled "Why You Should Care About Phase Transitions in Clustering" received more than +37 Google points, a record, while the list You are not paying attention if... generated about +6 Google points. We also saw several interesting sets of convergences

- one between speckle as observed in astronomy and those appearing on wall reflections yielding the ability to cheaply look around the corners ( Non-invasive real-time imaging through scattering layers and around corners via speckle correlations)
- another one on several fields looking at advanced matrix factorizations ( A Convergence of Interests: IEEE SP Mag, COLT2014 and more... )
- or that sensing and machine learning share common themes (From Direct Imaging to Machine Learning ... a rapid panorama (JIONC 2014)).

we also saw how random projections are slowly permeating into several avenues

- Compressive classification and the rare eclipse problem
- Random forests with random projections of the output space for high dimensional multi-label classification

I also mentioned a thing or two about the sociology of blogging (What Could Possibly Go Wrong ? Peer-Review, Trolls, Data Breaches) while reaching 3000th published posts. We also had about 15 implementations released by their respective authors, another record I think. Finally, we also had Another Sighting of Citing Nuit Blanche. Enjoy !

Implementations

- TGA: Grassmann Averages for Scalable Robust PCA
- Spectral redemption: clustering sparse networks
- Blind Image Deblurring by Spectral Properties of Convolution Operators
- Active Subspace: Towards Scalable Low-Rank Learning
- EMaC : Robust Spectral Compressed Sensing via Structured Matrix Completion
- Low-Rank Modeling of Local k-Space Neighborhoods (LORAKS): Implementation and Examples for Reproducible Research
- PETRELS: Parallel Subspace Estimation and Tracking by Recursive Least Squares from Partial Observations
- Confidence Intervals and Hypothesis Testing for High-Dimensional Regression
- LSR: Robust and Efficient Subspace Segmentation via Least Squares Regression
- IRNN: Generalized Nonconvex Nonsmooth Low-Rank Minimization
- CPCP: Scalable Robust Matrix Recovery: Frank-Wolfe Meets Proximal Methods
- Bayesian Pursuit Algorithms
- KNIFE: Automatic Feature Selection via Weighted Kernels and Regularization
- Summary of Contribution: Compressed sensing with linear correlation between signal and measurement noise
- STSBL-EM : Spatiotemporal Sparse Bayesian Learning with Applications to Compressed Sensing of Multichannel Physiological Signals

Focused Interests

- A Comparison of Clustering and Missing Data Methods for Health Sciences
- What Could Possibly Go Wrong ? Peer-Review, Trolls, Data Breaches
- Slides: Kernel Methods for Big Data
- Reconstructing Nonlinear Biochemical Networks
- A Convergence of Interests: IEEE SP Mag, COLT2014 and more...
- Random forests with random projections of the output space for high dimensional multi-label classification
- You are not paying attention if...
**+6** - Privacy Tradeoffs in Predictive Analytics
- Robust Subspace Recovery via Dual Sparsity Pursuit
- Sparse PCA: Covariance Thresholding and an AMP based approach
- Recent Developments in the Sparse Fourier Transform: A Fast DSP Chip and a faster GPS
- Compressive classification and the rare eclipse problem
- From Direct Imaging to Machine Learning ... a rapid panorama (JIONC 2014)
- SKA as an Atmosphere Monitoring Station ? - Part deux -
- Non-invasive real-time imaging through scattering layers and around corners via speckle correlations

Other

- Detection of the Gravitational Lens Magnifying a Type Ia Supernova
- It's Friday afternoon, it's Hamming's time: Antipode Seismic Maps ?
- 3000th post. Wow !

Machine Learning Meetups (slides and videos)

- Slides and Video: Zurich Machine Learning Meetup #2
- Slides and Video: Paris Machine Learning Meetup #10: Dolphin Communications, Big Data, ConvNets and Quantum Computers +8
- Ce Soir / Tonight: Paris Machine Learning Meetup #10: Dolphin Communications, Big Data, ConvNets and Quantum Computers
- Deep ConvNets; "Astounding" baseline for vision +5

Saturday Morning Videos

Meeting announcements:Jobs:

**Credit: ESA/NASA, Soho, LASCO 3**

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