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