Learning Linearized Assignment Flows for Image Labeling. (arXiv:2108.02571v2 [cs.LG] UPDATED)

We introduce a novel algorithm for estimating optimal parameters of
linearized assignment flows for image labeling. An exact formula is derived for
the parameter gradient of any loss function that is constrained by the linear
system of ODEs determining the linearized assignment flow. We show how to
efficiently evaluate this formula using a Krylov subspace and a low-rank
approximation. This enables us to perform parameter learning by Riemannian
gradient descent in the parameter space, without the need to backpropagate
errors …

arxiv image labeling learning