Because s c,i would not be used in other components of our framework, we integrate out s c,i and write the log likelihood as Note that o * c is a hidden variable but not a model parameter, and J T is the likelihood of ρ c,i = δ(o c,i = o * c ).
we would first infer o * c = argmax o * c J T , then train the true label discovery model by maximizing J T .