That is, given a training set D = { x y } of pairs of inputs x and output sequences y we need to learn the parameters {W } and {Z}.
for this purpose we will do standard max-likelihood estimation and find the parameters that minimize the conditional negative log-likelihood of the data in D. we will find the {W } and {Z} that mini-mize the following loss function L(D, {W }, {Z}): − x y ∈D logP (y|x; {W }, {Z}) Recall that we are interested in learning low-rank unary and binary potentials.