Since the last Nuit Blanche in Review (August 2016), Rosetta landed on a comet but we also had three Paris Machine Learning meetups, three reviews, two sunday morning insights, and many more in-depth entries. Enjoy !
Implementations
Sunday Morning Insights
In-depth:
- L1-PCA, Online Sparse PCA and Discretization and Minimization of the L1 Norm on Manifolds
- A Randomized Tensor Singular Value Decomposition based on the t-product
- Coherence Pursuit: Fast, Simple, and Robust Principal Component Analysis
- Large-Scale Strategic Games and Adversarial Machine Learning
- Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network
- Randomized single-view algorithms for low-rank matrix approximation
- Integrating multiple random sketches for singular value decomposition
- A Randomized Approach to Efficient Kernel Clustering
- Hamiltonian Monte Carlo Acceleration Using Surrogate Functions with Random Bases
- A Computationally Efficient Projection-Based Approach for Spatial Generalized Linear Mixed Models
- Convexified Convolutional Neural Networks
Paris Machine Learning Meetups
- Paris Machine Learning Meetup, Hors série #1: Introduction to Bayesian Inference with Stan and R
- Paris Machine Learning Meetup, Hors série #2: Scalable Machine Learning with H2O
- Paris Machine Learning #1 Season 4: AlphaGo, Deep Learning & Global Biodiversity, DataScience Game
- Paris Machine Learning Meetup Newsletter September 2016 [mostly in French]
Book/reviews/courses
- Book: Reinforcement Learning: An Introduction by Richard S. Sutton and Andrew G. Barto
- Low-Rank Tensor Networks for Dimensionality Reduction and Large-Scale Optimization Problems: Perspectives and Challenges PART 1
- Course: Data Science From data to knowledge (slides, codes, datasets...), Xavier Bresson
LightOn
Hamming's time
Meetings
CfP:
Videos
- Saturday Morning Videos: Plenary Panel: Is Deep Learning the New 42? at KDD 2016
- Saturday Morning Videos: Learning to learn and compositionality with deep recurrent neural networks, Nando de Freitas. KDD 2016
- Sunday Morning Video: Bay Area Deep Learning School Day 2 Live streaming
- Sunday Morning Videos: HORSE2016, On “Horses” and “Potemkin Villages” in Applied Machine Learning
- Saturday Morning Video: Bay Area Deep Learning School Day 1 Live streaming
- Saturday Morning Videos: Other plenary videos KDD2016 by Joe Hellerstein, Whitfield Diffie and Jennifer Chayes.
- Saturday Morning Video: A VC View of Investing in ML by Greg Papadopoulos, NEA (KDD 2016)
Jobs:
- CSjobs: Lecturers (Assistant Professors) in: Machine Learning & Computer Vision; Robot Vision & Autonomous Systems
- CSjobs: Two Ph.D. positions at TU Wien (Austria) and Aalto University (Finland)
- CSjobs: Several Post-Doctoral Research Associate Signal and Image Processing Institute, University of Southern California
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