Looking for a good resource on dimensionality reduction.

Hey everyone, I am looking for a paper/book/website/video that explains PCA, ICA and Kernel PCA - their derivation, meaning, and applications to improving supervised learning.

Also, even though it's not dimensionality reduction in the strictest sense, I would love to see a similar discussion of overcomplete sparse encoding.