Nuit Blanche in Review ( November 2014 )

Since the last Nuit Blanche in Review ( October 2014 ), we landed on a comet (ESA's 28 minutes of Terror : Philae's Landing on 67P, Yes, We Can Locate Philae and Here Is How ...). I also co-hosted the Paris Machine Learning #3 Season 2: Building a Data Science Team, Opinion Mining, Word2Vec, Kaggle and noticed some old way of performing robust PCA (The first ever Robust PCA applied in Imaging). The Sparse- and Low-Rank Approximation Wiki was featured and I came up with one Sunday Morning Insight:

• Sunday Morning Insight: It's Complicated...On Games, NP-hardness, Grothendieck, Learning and Friends.

 We also had quite a few -to say the least) implementations:

• Matrix Completion on Graphs - implementation -
• Spectral Clustering of Graphs with the Bethe Hessian - implementation -
• CKN: Convolutional Kernel Networks - implementation - 
• Compressive Sensing Reconstruction Solvers in Julia 
• LRSLibrary : 64 Algorithms for Low-Rank and Sparse for Background Modeling and Subtraction in Videos
• MatchLift : Near-Optimal Joint Object Matching via Convex Relaxation - implementation - 
• Zero SR1 quasi-Newton method - implementation - 
• CVXPY: A Python-Embedded Modeling Language for Convex Optimization Problems - implementation
• Convex Optimization in Julia 

 

Focused entries

• Accelerated NMR spectroscopy with low-rank reconstruction
• An ODE for solvers, a Group approach to regularizers, Sketching for Kernels and Linear Algebra, Johnson-Lindenstrauss is optimal, Coresets of Streaming Data  
• Convex Optimization for Big Data 
• Provable Bounds for Learning Some Deep Representations
• Nonlinear Information-Theoretic Compressive Measurement Design
• Riemannian Pursuit for Big Matrix Recovery
• Sparse Reinforcement Learning via Convex Optimization
• How to Scale Up Kernel Methods to Be As Good As Deep Neural Nets
• A Randomized Algorithm for CCA
• 3D Shape Reconstruction from 2D Landmarks: A Convex Formulation
• Neural Word Embeddings as Implicit Matrix Factorization
• Stable Autoencoding: A Flexible Framework for Regularized Low-Rank Matrix Estimation
• Nuclear Norm Minimization via Active Subspace Selection
• Randomized Interpolative Decomposition of Separated Representations 
• Dimensionality Reduction for k-Means Clustering and Low Rank Approximation

 

Job

• Two Postdoc positions ( KU Leuven ) ERC Advanced Grant A-DATADRIVE-B for 1-year, extendable at ESAT-STADIUS
• CS Internship in France: Compatibilité de l'apprentissage par représentations parcimonieuses et de la compression avec pertes / Compatibility between sparse machine learning and lossy compression
• Upcoming CSJobs and more ....

 Meetings / Slides / Videos / Cfps

• NIPS 2014 proceedings are out, what paper did you fancy ?
• Saturday Morning Videos: Big data and Data science: LIX colloquium 2014  
• Saturday Morning Videos: Machine Learning Summer School, Iceland 2014
• Slides : FOCS 2014 Workshop on The Sparse Fourier Transform: Theory and Applications
• Call for Papers : SPARS 2015 – Cambridge UK – 6-9 July 2015   

Books

• Book: Sparse Modeling for Image and Vision Processing
• Book: Regularization, Optimization, Kernels, and Support Vector Machines 

 

Other:

• Saturday Morning Video: Yielding of a Yogurt under constant stress 
• The researcher's article : a three-part adventure / Le chercheur et son article : une aventure en trois actes

Four image NAVCAM mosaic comprising images taken on 20 November. Credits: ESA/Rosetta/NAVCAM – CC BY-SA IGO 3.0

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