sparsity: Sparsity regularization

In fdavidcl/ruta: Implementation of Unsupervised Neural Architectures

Sparsity regularization

Description

Sparsity regularization

Usage

sparsity(high_probability, weight)

Arguments

high_probability	Expected probability of the high value of the encoding layer. Set this to a value near zero in order to minimize activations in that layer.
weight	The weight of the sparsity regularization

Value

A Ruta regularizer object for the sparsity, to be inserted in the encoding layer.

References

• Sparse deep belief net model for visual area V2

• Andrew Ng, Sparse Autoencoder. CS294A Lecture Notes

See Also

autoencoder_sparse, make_sparse, is_sparse

fdavidcl/ruta documentation built on July 5, 2023, 6:32 p.m.