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