Interpolation
Informed Source Separation
Spike super-resolution
Compressive Sensing
Structured sparsity
Regularization parameter
Régularisation
Phase Retrieval
Kernel mean embedding
Robustness
Données aberrantes
Modèles parcimonieux
Inverse problem
Low-complexity model
Super-resolution
Dimension reduction
Sketching
Principal component analysis
Sparse models
High dynamic range
Multi-image processing
Unsupervised learning
Mixture modeling
Random features
Index Terms-spike super-resolution
K-means
Random projection
Compressive Learning
Sparse recovery
Compressed sensing
Random moments
Super-résolution
Restricted isometry
Clustering
Projected gradient descent
Regularization
Excess risk control
Non-convex optimization
Semidefinite Programming
Random Fourier Features
Sparse signal
Statistical learning
Robustesse
Low dimensional models
Outliers