Something that could go by the same title is the use of tensor networks for ML. I think it works like a pre-optimization step by dimension reduction of the solu

Something that could go by the same title is the use of tensor networks for ML. I think it works like a pre-optimization step by dimension reduction of the solution space, but if someone could give the right intuitive explanation I'd be much obliged. It seems to be a way to lessen inductive bias by making decisions about available ML algos. That is, it vastly increases the solution space but remains effective by omitting unlikely solutions.