Convexifying Sparse Interpolation With Infinitely Wide Neural Networks: An Atomic Norm Approach.
Akshay KumarJarvis D. HauptPublished in: IEEE Signal Process. Lett. (2020)
Keyphrases
- neural network
- sparse sampling
- low rank matrices
- mixed norm
- robust principal component analysis
- group lasso
- regularized least squares
- sparse representation
- pattern recognition
- sparse data
- compressed sensing
- multilayer perceptron
- multi layer
- compressive sensing
- artificial neural networks
- neural network model
- objective function
- wide range
- linear interpolation
- back propagation
- image interpolation
- regression model
- fault diagnosis
- self organizing maps
- neural nets
- feed forward
- activation function
- training process
- low rank approximation
- high dimensional
- finite number
- fuzzy systems
- super resolution
- multi task
- norm regularization
- compressive sampling
- genetic algorithm