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
- 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 -
- 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
- 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
- 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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