Of generic interest and in support of open architectures, Shogun has been admitted into the Google Summer of Code 2013 and here are some of the ideas that students can work on. I need to produce something for them sooner rather than later. In any case, some of you might be interested in the FastFood development (here) and other related projects. Stay tuned.

I noted two courses in German and French that use Nuit Blanche as a reference material for their students. At long last, world domination, muahahahahah:

The reason we created some groups is for them to be place of exchange, so far we have the Google+ Community (319 members), the CompressiveSensing subreddit (103 members), the LinkedIn Compressive Sensing group (2189 members) or the Matrix Factorization (630 members) and the Calibration Club (35 members). Those groups are there for you to share your work or any other information with like minded people. Recently. in the Reddit group we discovered a compressive sampling overview in Python. In the LinkedIn Group on compressive Sensing, Pierre asked a question on Sparse representations of EEG ?, Alaa asked about compressive sensing summer school and I asked a question on Analysis operator for signals other than visible photon imaging ?. In the Google+ group, Thomas points to a poster on Compressed Sensing in Wireless Communication. In the Google+ group you may want to feature your papers and ask question directly in the discussion section.

Since the last Around the blogs in 78 hours, here is what popped up on the blogs:

Sebastien

- ORF523: Conditional Gradient Descent and Structured Sparsity
- A new book on Concentration Inequalities by Boucheron, Lugosi and Massart
- Guest post by Amir Ali Ahmadi: Sum of Squares (SOS) Techniques: An Introduction, Part II/II
- Guest post by Amir Ali Ahmadi: Sum of Squares (SOS) Techniques: An Introduction, Part I/II
- ORF523: Strong convexity
- ORF523: Nesterov’s Accelerated Gradient Descent
- ORF523: Oracle complexity of smooth convex functions
- ORF523: Oracle complexity of Lipschitz convex functions
- ORF523: Oracle complexity, large-scale optimization

Masaaki

Danny

Hein

Hackaday

Larry

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.

Danny

Hein

- “Autoencoders, MDL, and Helmholtz Free Energy”
- Deriving the Gaussian Distribution from the Sterling Approximation and the Central Limit Theorem
- A new Dalton Minimum ? (Off topic)

Hackaday

Larry

- Super-efficiency: “The Nasty, Ugly Little Fact”
- Topological Inference
- Amanda Knox and Statistical Nullification

- Bayesian computational tools
- painful truncnorm
- Bayesian non-parametrics
- in praise of the referee (or not)

In the meantime, on Nuit Blanche, we had the following entries:

- Model-Based Calibration of Filter Imperfections in the Random Demodulator for Compressive Sensing - implementation -
- The Long Post of the Month (Part I)
- MOUSSE: Multiscale Online Union of SubSpaces Estimation - implementation -
- Sunday Morning Insight: How to spot a compressive sensing system, the case of Fourier Transform Infra-Red Spectroscopy
- Saturday Morning Videos
- Structural Information in Nanopore Sequencing ?
- 19 months of Reproducible Research
- GESPAR: Efficient Phase Retrieval of Sparse Signals and QCS: Sparsity based sub-wavelength imaging) -implementations-
- Matheon-Workshop "Compressed Sensing and its Applications" and Compressed Sensing applied to Radar (CoSeRa 2013)
- Faster Randomized Kaczmarz
- Toward real-time quantum imaging with a single pixel camera
- Graphlab Workshop on Large Scale Machine Learning 2013
- Nuit Blanche in Review (March 2013)
- Videos: 2012 IPAM Graduate Summer School: Deep Learning, Feature Learning
- The Space of Solutions of Coupled XORSAT Formulae
- Living on the edge: A geometric theory of phase transitions in convex optimization
- A Note on k-support Norm Regularized Risk Minimization -implementation -
- Inductive Sparse Subspace Clustering - implementation - and Greedy Feature Selection for Subspace Clustering
- Post-doctoral fellowship at Harvard Medical School: diffusion MRI and functional MRI

**Join the CompressiveSensing subreddit or the Google+ Community and post there !**

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.

## No comments:

Post a Comment