Table 7.

Algorithm: Mean field annealing

\SetKwInOut{Input}{Input}

\SetKwInOut{Output}{Output}

\Input{A set of observations (tij, sij) for each pair (i, j), ψ, a number of clusters K}

\Output{A probability qik for a node i belonging to a cluster k for all i and for all k}

Initialize q to random values;

Initialize annealing factor γ;

Whileγ <γmax Repeatq converges

ForAlli ∈ V

ForAllk ∈ K

$C_{ik}={\displaystyle \sum _{j\in Neighbor(i)}{q}_{jk}(t_{ij}-s_{ij})+(1-q_{jk})\psi s_{ij}}$

ForAllk ∈ K

${\widehat{q}}_{ik}=\frac{\exp (-\gamma C_{ik})}{{\displaystyle \sum _{l=1}^K\exp (-\gamma C_{il})}}$

ForAllk ∈ K

qik = ${\widehat{q}}_{ik}$

Increase γ;