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