In an article by Hofmann pdf, he proposes:
initialize $β$ to one, run until convergence, then rescale $β$ by a factor $η<1$, run again until convergence, and iterate this until changing $β$ no longer improves the result.
I used the TEM algorithm on a dataset for my project, but the problem is that the algorithm ends up traped in several local minima and doesn't give me full convergence. My question is: what is the optimal condition under which I can assume that the algorithm converged?