Since the last Nuit Blanche in Review (January 2017), we've had quite a few exciting implementations, several in-depth papers, one thesis, some activity on the conference front, four Machine Learning meetups in Paris (and a newsletter), two jobs opening and a few videos. Enjoy !

Implementations

In-depth

- Phase Transitions in Oblivious Compressed Sensing
- The Rare Eclipse Problem on Tiles: Quantised Embeddings of Disjoint Convex Sets
- Automatic Parameter Tuning for Image Denoising with Learned Sparsifying Transforms
- Learning to Invert: Signal Recovery via Deep Convolutional Networks
- Deep Learning to Hash: HashNet and DHN
- The Power of Sparsity in Convolutional Neural Networks
- Randomness in Neural Networks: An Overview
- A Random Matrix Approach to Neural Networks
- Net-Trim: A Layer-wise Convex Pruning of Deep Neural Networks / BranchHull: Convex bilinear inversion from the entrywise product of signals with known signs
- Wasserstein Training of Restricted Boltzmann Machines

Thesis

Conferences:

Paris Machine Learning Meetups

- Ce soir: Paris Machine Learning Hors Serie #8 Season 4: Azure Machine Learning
- Ce soir: Paris Machine Learning, Hors serie #7 Season 4: Machine Learning for Arts, Gene Kogan
- Ce soir: Paris Machine Learning #6 season 4, Symbolic AI, Recommendations & Naïve Bayes
- Today: Paris Machine Learning, Hors série #5 Season 6: : See.4C Spatio-temporal Series Hackathon

Job

Videos:

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