Nuit Blanche in Review ( January 2015 )

Since the last Nuit Blanche in Review ( December 2014 ), we provided a Short Review of 2014 on Nuit Blanche and another quick review of the Paris Machine Learning Meetup in 2014 as well as three Sunday Morning insights:

• Sunday Morning Insight: The Hardest Challenges We Should be Unwilling to Postpone
• Sunday Morning Insight: What Happens When You Cross into P Territory ?
• Sunday Morning Insight: The Great Convergence ?

We also had two Paris Machine Learning Meetups:

• Paris Machine Learning Meetup "Hors Série" 2 (Season 2) Data Science for Non-Profits
• Paris Machine Learning Meetup #5 Season 2, Time Series and FinTech, Adversarial Algos

and saw a new way of doing peer review for a conference:

• The papers for ICLR 2015 are now open for discussion !

We also had quite a few implementations made available by their authors:

• Convex Cardinal Shape Composition (CCSC) - implementation -
• REMBO : Bayesian Optimization in a Billion Dimensions via Random Embeddings - implementation -
• Recovery from Linear Measurements with Complexity-Matching Universal Signal Estimation - implementation -
• Phase recovery from a Bayesian point of view: the variational approach - implementation - 
• Smoothed Low Rank and Sparse Matrix Recovery by Iteratively Reweighted Least Squares Minimization - implementation -
• LatLRR : Robust latent low rank representation for subspace clustering - implementation -
• MORESANE: MOdel REconstruction by Synthesis-ANalysis Estimators. A sparse deconvolution algorithm for radio interferometric imaging - implementation
• Frequency Selective Compressed Sensing - implementation -
• BlockPR: Fast Phase Retrieval for High-Dimensions - implementation -
• FASTA: A Field Guide to Forward-Backward Splitting with a FASTA Implementation - implementation
• Positive Low-Rank Tensor Completion - implementation -

Thesis:

• Thesis: Synthetic Aperture Radar Tomography: Compressed Sensing Models and Algorithms, Esteban Aguilera

Other focused entries going from Machine Learning typeof topics to Compressive Sensing ones and finishing by hardware related topics:

• Improving approximate RPCA with a k-sparsity prior
• Unbiased Bayes for Big Data: Paths of Partial Posteriors / Computing Functions of Random
• Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels
•  Fast, simple and accurate handwritten digit classification using extreme learning machines with shaped input-weights 
• Why does Deep Learning work? - A perspective from Group Theory
• Speeding-up Convolutional Neural Networks Using Fine-tuned CP-Decomposition
• Unbiased Bayes for Big Data: Paths of Partial Posteriors / Computing Functions of Random Variables via Reproducing Kernel Hilbert Space Representations
• Compressing Deep Convolutional Networks using Vector Quantization
• In Search of the Real Inductive Bias: On the Role of Implicit Regularization in Deep Learning
• New Ranks for Even-Order Tensors and Their Applications in Low-Rank Tensor Optimization
• Efficient Blind Compressed Sensing and $\ell_0$ Sparsifying Transform Learning
• Inference for Generalized Linear Models via Alternating Directions and Bethe Free Energy Minimization
• A note on ADMM-GAMP
• A robust sub-linear time R-FFAST algorithm for computing a sparse DFT
• Sparse Solutions to Nonnegative Linear Systems and Applications
• Random Matrices for the People: An Introduction to Matrix Concentration Inequalities 
• Cloud K-SVD: A Collaborative Dictionary Learning Algorithm for Big, Distributed Data
• Approximate Subspace-Sparse Recovery in the Presence of Corruptions via $\ell_1$-Minimization
• Lifting for Blind Deconvolution in Random Mask Imaging: Identifiability and Convex Relaxation / Learning to Deblur 
• Pose estimation using time-resolved inversion of diffuse light
• Holistic random encoding for imaging through multimode fibers
• Random Calibration for Accelerating MR-ARFI Guided Ultrasonic Focusing in Transcranial Therapy

Meetings/CfPs/Abstracts/Videos of meetings

• Workshop on Big Data and Statistical Machine Learning, January 26 – 30, 2015
• CfP: "Applications of Matrix Computational Methods in the Analysis of Modern Data” Workshop Reykjavik, Iceland , June 1-3, 2015
• Proceedings: Biomedical and Astronomical Signal Processing (BASP) Frontiers Workshop 2015
• Saturday Morning Videos: Videos and Slides of the 2014 Workshop on Sensing and Analysis of High-Dimensional (SAHD) meeting
• CSMeeting: Compressed Sensing in Wireless Communication - Workshop 2015
• Gene Golub SIAM Summer School 2015 RandNLA: Randomization in Numerical Linear Algebra Delphi, Greece (June 15-26, 2015)
• 2nd CfP: SPARS 2015 Signal Processing with Adaptive Sparse Structured Representations

Videos:

• Saturday Morning Video: Gigapixels of Andromeda, NVIDIA and CNNs at CES and some light hearted late night comedy

Other:

• One must imagine Charlie happy
• Charlie

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