The stacked sparse autoencoder is a powerful deep learning architecture composed of multiple autoencoder layers, with each layer responsible for extracting features at different levels.

In deep learning models, overfitting refers to the phenomenon where a model performs well on training data but poorly on unseen samples. To avoid this, HOLO randomly drops a subset of neurons during ...