Table 1 shows in detail the percentages of the training time (see the numbers in brackets) spent at each sampling step for gSLDA+.
it is non-trivial to develop a Gibbs sampling algorithm using the similar data augmentation idea, due to the presence of latent variables and the nonlinearity of the soft-max function.