Happy New Year 2017 ! Since the Nuit Blanche in Review (November 2016), NIPS2016 happened and a few other important things ! As a reminder, we are still in this period of intense intellectual wandering, What Are You Waiting For ?

This past month, we also had a few implementations:

- Learning the nonlinear geometry of high-dimensional data: Models and algorithms - implementation
- DataSketches : Sketches Library from Yahoo! - implementation -
- SketchMLbox: A MATLAB toolbox for large-scale mixture learning - implementation - ( Compressive K-means , Sketching for Large-Scale Learning of Mixture Models )
- Linearly Convergent Randomized Iterative Methods for Computing the Pseudoinverse -implementation -
- Thesis: Sketch and Project: Randomized Iterative Methods for Linear Systems and Inverting Matrices - implementation -
- Onsager-Corrected Deep Networks for Sparse Linear Inverse Problems - tensorflow implementation-

Some in-depth blog entries:

- Sparse Label Propagation
- Efficient Methods for Deep Neural Networks
- Interpretable Recurrent Neural Networks Using Sequential Sparse Recovery
- Distributed Sequence Memory of Multidimensional Inputs in Recurrent Networks

Two theses

- Thesis: Sketch and Project: Randomized Iterative Methods for Linear Systems and Inverting Matrices - implementation -
- Thesis: Uncertainty in Deep Learning by Yarin Gal

A few entries covering NIPS2016

- #NIPS2016: Interpretable Machine Learning for Complex Systems Workshop
- 22 implementations of #NIPS2016 papers
- Efficient Methods for Deep Neural Networks
- Interpretable Recurrent Neural Networks Using Sequential Sparse Recovery
- Distributed Sequence Memory of Multidimensional Inputs in Recurrent Networks
- Some general takeaways from #NIPS2016
- Spotlight videos at #NIPS2016
- Videos at #NIPS2016, and other news and announcements
- What to do in Barcelona this week, #NIPS2016 edition

Paris Machine Learning meetup

Slides:

- Slides: Annual Paris-Saclay Center for Data Science Pitching Day
- Slides: New Directions for Learning with Kernels and Gaussian Processes, Dagstuhl Seminar

Jobs:

- Internship: Signal and image classification with invariant descriptors (scattering transforms), IFPEN Rueil Malmaison, France
- Job: Data scientist: deep learning approaches to microbial genomics, Institut Pasteur, Paris
- Job: Data Scientist Position, Paris-Saclay Center for Data Science (CDS), France
- Job: Postdoc Position in Machine Learning for Health Sensing, MIT
- CSjob: PhD. position, Compressed sensing in transmission electron microscopy, EMAT, Antwerp, Belgium

Saturday Morning Videos:

- Saturday Morning Videos: Learning, Algorithm Design and Beyond Worst-Case Analysis workshop, Simons Institute, Berkeley
- Saturday Morning Video: Deep Compression, DSD Training and EIE: Deep Neural Network Model Compression, Regularization and Hardware Acceleration by Song Han

Conferences:

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

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