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.

HOLO has innovated and optimized the stacked sparse autoencoder by utilizing the DeepSeek model. This technique employs a greedy, layer-wise training approach, optimizing the parameters of each ...