Nuit Blanche in Review (May 2016)

Since the last Nuit Blanche in Review (April 2016), we've been witness to the  Mercury Transit of 2016 .
I started a proposal for a NIPS Workshop or Symposium on "Mapping Machine Learning to Hardware". We also had an astrounding 80 implementations being made available and a very large number of saturday morning videos. Enjoy !

Implementations:

• 74 implementations released from #ICLR2016 papers !
• TensorNet : Tensorizing Neural Networks - implementation -
• Riemannian stochastic variance reduced gradient on Grassmann manifold - implementation -
• Thesis: Ristretto: Hardware-Oriented Approximation of Convolutional Neural Networks - implementation -
• Dictionary Learning for Massive Matrix Factorization - implementation -
• Probabilistic Integration: A Role for Statisticians in Numerical Analysis? - implementation -
• Low Dimensionality in Gene Expression Data Enables the Accurate Extraction of Transcriptional Programs from Shallow Sequencing - implementation -

Hardware

• ASP Vision: Optically Computing the First Layer of Convolutional Neural Networks using Angle Sensitive Pixels
• Follow-up to 'Making Hyperspectral Imaging Mainstream'
• Multimode waveguide speckle patterns for compressive sensing

In depth

• Review: RandNLA: Randomized Numerical Linear Algebra
• Hyperspectral Blind Reconstruction From Random Spectral Projections
• Harvesting Nature: from Computational Imaging to Optical Computing
• The Shallow Side of Deep Learning
• Fast nonlinear embeddings via structured matrices
• Towards Conceptual Compression
• Compressively characterizing high-dimensional entangled states with complementary, random filtering
• FISTA and "Maximal Sparsity with Deep Networks?", Learning MMSE Optimal Thresholds for FISTA
• Phase Retrieval: Robust phase retrieval with the swept approximate message passing (prSAMP) algorithm / On The 2D Phase Retrieval Problem
• Distributed Sequence Memory of Multidimensional Inputs in Recurrent Networks
• Maximal Sparsity with Deep Networks?
• Performance Trade-Offs in Multi-Processor Approximate Message Passing
• Performance Limits for Noisy Multi-Measurement Vector Problems
• Computing Active Subspaces Efficiently with Gradient Sketchibg
• Fast nonlinear embeddings via structured matrices
• Matrix Factorization, Random Features, Hashing Kernels roundup
• Training Neural Networks Without Gradients: A Scalable ADMM Approach

Thesis

• PhD Thesis: Sparse and low rank signal recovery with partial knowledge, Jinchun Zhan

Meetings/Meetups

• COLT 2016 accepted papers
• ICML 2016 accepted papers are out !
• Ce soir: Paris Machine Learning Meetup #13 Season 3; Data augmentation methods in Deep Learning, Neural Turing Machines, Manga Recommendation
• Meeting (in French) Co-conception de systèmes hybrides : quand l'instrumentation et les traitements numériques se rencontrent., June 17th, 2016
• @ICLR2016 Periscopes / 4th edition of CoSeRa / ITWIST'16 registration is now open / Workshop on “Networks: learning, information and complexity” at the Institut Henri Poincaré, Paris, May 18-20, 2016.

Videos

• Saturday Morning Videos: International Conference on Learning Representations (ICLR) 2016, San Juan
• Saturday Morning VideoS: Random Instances and Phase Transitions Workshop @ Simons Institute
• Saturday Morning Video: Solvable Model of Unsupervised Feature Learning, Lenka Zdeborova @ Simons Institute
• Video: P vs. NP and the Computational Complexity Zoo
• Saturday Morning Video: Linear Inverse Problems, Ankur Moitra @CIRM
• Saturday Morning Video: A Polynomial Time Algorithm for Lossy Population Recovery, Ankur Moitra @CIRM
• Saturday Morning Video: Tensor Decompositions and their Applications, Ankur Moitra @CIRM
• Saturday Morning Video: Algorithmic Aspects of Inference, Ankur Moitra @CIRM
• Saturday Morning Video: From Pigeons to Fano, and beyond, Suresh Venkatasubramanian at IHP
• Saturday Morning Video: Near-optimal message-passing algorithms for crowdsourcing, Sewoong Oh at IHP
• Saturday Morning Video: Factor Graphs, Belief Propagation, and Density Evolution, Henry Pfister
• Saturday Morning Video: An Optimal Affine Invariant Smooth Minimization Algorithm, Alexandre d'Aspremont at IHP
• Saturday Morning Video: Understanding Phase Transitions in Compressed Sensing, Galen Reeves at IHP
• Saturday Morning Video: New Algorithms for Heavy Hitters in Data Streams, David Woodruff at IHP
• Saturday Morning Video: Group-testing: Together we are one, Sidharth Jaggi at IHP
• Saturday Morning Video: Stream, sketching and Big Data, Graham Cormode at IHP
• Saturday Morning Video: Dynamics of Randomized Row-Action Methods for High-Dimensional Estimation, Yue Lu at IHP
• Saturday Morning Video: Sketching and Embeddings , Alex Andoni at IHP
• Saturday Morning Video: New Algorithmic Techniques for Massives graphs, Andrew McGregor at IHP
• Saturday Morning Video: "Computational thinking, inferential thinking and Big Data" by Mike Jordan
• Saturday Morning Video: "Beyond Matrix Completion" by Ankur Moitra

Other videos:

• 32 Minutes of Earth From Space
• Saturday Morning Video: Proving them wrong, Space X First-stage landing from the Onoard Camera
• Saturday Morning Video: James Webb Space Telescope Mirror Rollover Timelapse

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