and the gradient of the log-probability works out to: For the complete derivation, see Appendix C. The parameters θ of the adjustment function are learned by maximizing the Poisson log-probability, using stochastic gradient ascent.
for each feature-target pair (f, t) we compute the gradient in Eq.