Nuit Blanche in Review ( April 2015 )

NASA / JHUAPL / SwRI



In the past month, we witnessed the first images of Pluto with a resolution never attained before thanks to the New Horizon mission  and last night, we bid farewell to the Messenger spacecraft as it crashed on Mercury.

Well I guess it is time to say goodbye to all my friends, family, support team. I will be making my final impact very soon.

— MESSENGER (@MESSENGER2011) April 30, 2015

Since the last Nuit Blanche in Review ( March 2015 ), we had quite a few hardware related papers:

• Task-driven Adaptive Sensing on Quadrupole Mass Filter Systems for Classification
• High-speed flow microscopy using compressed sensing with ultrafast laser pulses
• FPA-CS: Focal Plane Array-based Compressive Imaging in Short-wave Infrared
• Sparse Signal Processing Concepts for Efficient 5G System Design
• The Glitter Telescopes
• GPU Accelerated Randomized Singular Value Decomposition and Its Application in Image Compression

and quite a few implementations:

• Saturday Morning Video: Towards a Learning Theory of Causation - Implementation -
• Finding a sparse vector in a subspace: Linear sparsity using alternating directions - implementation -
• SLOPE is Adaptive to Unknown Sparsity and Asymptotically Minimax - implementation -
• Complete Dictionary Recovery over the Sphere - implementation -
• SOOT l1/l2 norm ratio sparse blind deconvolution - implementation -

Some in-depth studies

• Compressed Sensing Petrov-Galerkin Approximations for Parametric PDEs
• Co-L1/Co-IRWL1: Iteratively Reweighted $\ell_1$ Approaches to Sparse Composite Regularization
• Streaming: Memory Limited Matrix Completion with Noise, Verifiable Stream Computation, Count-Min-Log sketch
• Scale Up Nonlinear Component Analysis with Doubly Stochastic Gradients
• Compressed Sensing Recovery via Nonconvex Shrinkage Penalties
• Dictionary Learning with Few Samples and Matrix Concentration
• Tensor machines for learning target-specific polynomial features
• Generating a New Reality with Deep Architectures
• AMP solvers and the Additive White Gaussian Noise Channel
• Efficient Dictionary Learning via Very Sparse Random Projections
• Sparse inversion of Stokes profiles. I. Two-dimensional Milne-Eddington inversions
• A Probabilistic Theory of Deep Learning

related to Paris ML meetups

• AutoML Challenge: Python Notebooks for Round 1 and more...
• Paris Machine Learning Meetup #8, Season 2: Deep Learning and more...

Slides

• Statistical Image Recovery: A Message-Passing Perspective by Phil Schniter
• Slides: Stephen Boyd's Russell Severance Springer Lectures on Convex Optimization
• Video and Slides: Learning Sparse Data with Near-optimal Speed and Efficiency from a Variety of Measurement Processes
• Video and Slides: Sketching for M-Estimators: A Unified Approach to Robust Regression, David Woodruff
• Video and Slides: Simple, Efficient and Neural Algorithms for Sparse Coding, Ankur Moitra

CfPs

• ICML Workshop on Machine Learning Open Source Software 2015: Open Ecosystems
• CfP: Structured Matrices in Signal and Data Processing, IEEE J-STSP special issue

Thesis

• Thesis: Empirical-Bayes Approaches to Recovery of Structured Spar se Signals via Approximate Message Passing, Jeremy Vila
• Thesis: Turning Big Data into Small Data, Hardware Aware Approximate Clustering with Randomized SVD and Coresets, Tarik Adnan Moon

Job

• CSJob: Post-Doc: Learning Representations for Large Scale Multivariate Data
• CSJob: 18 Funded PhD opportunities (ESRs) in Machine Sensing (Machine Learning, Sparse Representations and Compressed Sensing)
• CSJob: Joint EPFL/Inria postdoc: Fast Transforms on Graphs (applications until the end of April 2015)
• CSJob: PhD Position – Exploration of wiring diagnostics via compressive sensing: Algorithms and ultra-compact Analog-to-Information (A2I) architectures

Videos

• Saturday Morning Videos: RE.WORK Deep Learning Summit, San Francisco, 2015
• Saturday Morning Videos: Information Theory, Learning and Big Data @ Simons Institute, Berkeley
• Saturday Morning Video: Tensor Methods for Feature Learning, Constructing Informative Features for Discriminative Learning by Animashree Anandkumar
• Video: Statistical Estimation on Graphs, Andrea Montanari
• Video and Slides: Learning Sparse Data with Near-optimal Speed and Efficiency from a Variety of Measurement Processes
• Video and Slides: Sketching for M-Estimators: A Unified Approach to Robust Regression, David Woodruff
• Video and Slides: Simple, Efficient and Neural Algorithms for Sparse Coding, Ankur Moitra

Other

• Three biographies: Ken Case, Charles Johnson and Leo Breiman
• 8 days of Nuit Blanche
• iLab, IFPEN, Paris Machine Learning Meetups this April

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