unobserved) and that the topic and word distributions θ and φ are drawn from Dirichlet distributions: θ ∼ Dir(α), and φ ∼ Dir(β).
using this model, one can attempt to infer the most likely topics to generate a corpus for some preset number of topics K. the optimization problem is non-convex and intractable to solve analytically, and is thus generally solved using iterative techniques such as Gibbs sampling, expectation maximization, or variational inference.