Determination of maximum likelihood tree $T^*$ given cascade $c$ on graph $G$.
To me, the main insight to solve this problem is to realize that $T^*$ identification given $c$, $G$ can be efficiently performed by a node-wise optimization of the active nodes in $c$ (i.e. any active node has exactly one infection source). On the other hand, I am not entirely certain whether $w(i,j) = \log(P'(i,j))-\log(\epsilon)$ (preprint on arXiv) or $w(i,j) = \log(P'(i,j))-\log(\epsilon P(i,j))$ (KDD '12) is actually the right weight to use. It seems to me that we ought to use $w(i,j)=\log(P'(i,j))$ directly, and that we don't necessarily have to make the approximation of Eq. 11 (i.e. assuming all unactivated edges are $\epsilon$-edges). Let me try out my idea first.
