 Dimensionality Reduction was one of the first applications of deep learning, and one of the early motivations to study autoencoders.In a nutshell, the objective is to find a proper projection method, that maps data from high feature space to low feature space.One milestone paper on the subject was that of Geoffrey Hinton with his publication in Science Magazine in 2006