Deep Semi-Random Features for Nonlinear Function Approximation
Deep Semi-Random Features for Nonlinear Function Approximation
We propose semi-random features for nonlinear function approximation. The flexibility of semi-random feature lies between the fully adjustable units in deep learning and the random features used in kernel methods. For one hidden layer models with semi-random features, we prove with no unrealistic assumptions that the model classes contain an …