Sparse-grid sampling recovery and deep ReLU neural networks in high-dimensional approximation.
Dinh DungVan Kien NguyenPublished in: CoRR (2020)
Keyphrases
- high dimensional
- neural network
- sparse data
- parameter space
- low dimensional
- sparse sampling
- dimensionality reduction
- low rank approximation
- sparse coding
- similarity search
- variable selection
- feature space
- approximation algorithms
- fuzzy logic
- high dimension
- compressive sensing
- high dimensionality
- pattern recognition
- compressive sampling
- uniform sampling
- failure recovery
- data points
- random sampling
- genetic algorithm
- error bounds
- nearest neighbor
- artificial neural networks
- closed form
- additive models
- sparse approximation
- importance sampling
- fault diagnosis
- generalized linear models
- multi dimensional
- neural network model
- image reconstruction
- random projections
- recurrent neural networks
- sample size
- back propagation
- feature extraction
- orthogonal matching pursuit
- grid computing
- gene expression data