The algorithm minimizes the following cost function: where e z is the error for a target node z defined as the squared difference between the final score assigned to z by the graph walk, p z , and some ideal score according to the example's labels, p Opt z .
4 p Opt z is set to 1 in case that the node z is relevant or 0 otherwise.