According to what I found, dimensionality reduction has two types feature selection and feature extraction . In feature extraction, we find PCA, LDA ,LLE , ISOMAP, etc.. In other works i find random projection, subspace tracking , sketching , low rank matrix approximation. I don’t have a big knowledge in this field neither in algebra but I think those notation are related. Are subspace tracking, sketching, low rank matrix approximation methods of feature extraction like pca etc. Or they are what?