Furthermore, we can take better control of the training procedure with trace regularization, e.g., encouraging larger trace(T) for reliable subset and smaller trace(T) for less relaibale ones.
we propose to minimize: where β m is the regularization weight for the m-th data subset, M is the total number of subsets, N m the number of instances in m-th subset, and T mi , y mi and o mi,y mi are the transition matrix, the relation labeled by DS and the observed probability of this relation for the i-th training instance in the m-th subset, respectively.