Since the last Nuit Blanche in Review ( July 2015 ) we saw the birth of GitXiv and a few implementations.

We also had some in-depth studies, with in particular some on-going clues of The Great Convergence in action as well as some compressive sensing hardware:

Credit: NASA/Johns Hopkins University Applied Physics Laboratory/Southwest Research Institute

- GitXiv: Because People Still Don't Care About You and Your Algorithm
- Machine Learning and Homomorphic Encryption
- Mash: Fast genome distance estimation using the MinHash algorithm
- Light Field Reconstruction Using Sparsity in the Continuous Fourier Domain
- ranger: A Fast Implementation of Random Forests for High Dimensional Data in C++ and R
- Manitest: Are classifiers really invariant?
- Low-Rank Spectral Optimization
- Fast Robust PCA on Graphs
- Consistent Signal and Matrix Estimates in Quantized Compressed Sensing
- Robust Principal Component Analysis on Graphs

We also had some in-depth studies, with in particular some on-going clues of The Great Convergence in action as well as some compressive sensing hardware:

- Toward a unified theory of sparse dimensionality reduction in Euclidean space
- Comparative Analysis of Scattering and Random Features in Hyperspectral Image Classification
- Distributed Compressive Sensing: A Deep Learning Approach
- Random Noise in the GoogleLeNet Architecture
- Cuckoo Linear Algebra
- Expander $\ell_0$-Decoding
- Efficient Compressive Phase Retrieval with Constrained Sensing Vectors
- SAFFRON: A Fast, Efficient, and Robust Framework for Group Testing based on Sparse-Graph Codes
- The LASSO with Non-linear Measurements is Equivalent to One With Linear Measurements
- A Randomized Rounding Algorithm for Sparse PCA
- A Deep Learning Approach to Structured Signal Recovery
- Single-sensor multispeaker listening with acoustic metamaterials / Spectral-temporal compressive imaging
- The inverse fast multipole method: using a fast approximate direct solver as a preconditioner for dense linear systems

- CSjob: Internship Opening: Nonlinear Dynamics and Control, MERL
- CSJob: Faculty, Chancellor's Faculty Excellence Program, NC State.

- Thesis: Message Passing and Combinatorial Optimization, Siamak Ravanbakhsh
- Thesis: Shallow and Deep Learning for Audio and Natural Language Processing, Po-Sen Huang

- Videos: Summer School on Hashing: Theory and Applications, 2014
- Saturday Morning Video: Machine Learning with Scikit Learn, Andreas Mueller & Kyle Kastner, SciPy 2015 Tutorial
- Slides; Deep Learning Summer School 2015
- Slides: KDD2015 Tutorials
- Proceedings SIGGRAPH 2015 and interesting papers
- Slides: Beating the Perils of Non-Convexity: Training Neural Networks using Tensor Methods
- Videos and Slides: Statistical Machine Learning course at CMU, Ryan Tibshirani and Larry Wasserman, Spring 2015
- Video: Deep Learning by Geoff Hinton, University of Cambridge, June 29th, 2015
- Saturday Morning Video: Dark Knowledge, Geoff Hinton
- Saturday Morning Video: A Mouse Brain
- Saturday Morning Video: Reinforcement Learning, David Silver
- Saturday Video Morning: Machine Learning Summer School Sydney 2015 (Slides and videos)

Credit: NASA/Johns Hopkins University Applied Physics Laboratory/Southwest Research Institute

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