Multilinear subspace learning

Multilinear subspace learning is a way of looking at data to try and make better predictions. It looks at a set of data points and tries to find patterns in them. For example, if you want to predict what will happen to the stock market next, you might use multilinear subspace learning to look at data from the stock market over the past few days and try to find patterns. Then, you can use the patterns to better predict what will happen in the future. It is like trying to figure out how a jigsaw puzzle fits together without actually looking at the pieces.