With regular distributive law you can do things like
$$\sum_{x_1,x_2,x_3} \exp(x_1 + x_2 + x_3)=\sum_{x_1} \exp x_1 \sum_{x_2} \exp x_2 \sum_{x_3} \exp x_3$$
This breaks the original large sum into 3 small sums which can be computed independently.
A more realistic scenario requires factorization into overlapping parts. For instance take the following
$$\sum_{x1,x2,x3,x_4,x_5} \exp(x_1 x_2 + x_2 x_3 + x_3 x_4+x_4 x_5)$$
You can't use directly apply distributive law here. Naive evaluation of the sum is exponential in the number of variables, however this problem can be solved in time linear in the number of variables.
Consider the following factorization
$$\sum_{x1,x2} \exp x_1 x_2 \left( \sum_{x_3} \exp x_2 x_3 \left( \sum_{x_4} \exp x_3 x_4 \left( \sum_{x_5} \exp x_4 x_5 \right) \right) \right) $$
Now note that when computing inner sums, naive approach results in same sum being recomputed many times. Save those shared pieces and you get an algorithm that's quadratic in number of variable values and linear in number of variables
Viterbi and Forward-Backward are specific names of this kind of dynamic programming for chain structured sums as above.
To consider tree-structured sum, take a problem of counting independent sets in a tree-structured graph. In this case we can use the following factorization
This is the first step of the recursion and you can repeat it until your pieces have tractable size.
Now for a general case of non-tree-structured graph, consider the sum below
$$\sum_{x1,x2,x3,x_4,x_5} \exp( x_1 x_2 + x_2 x_3 + x_3 x_4+x_4 x_5 + x_5 x_1 )$$
Here, variables form a loop, so regular tree recursion like Viterbi does not apply. However, this sum can be found efficiently, linear in the number of variables, and cubically in the number of variable values. I have more in depth explanation of decomposing problems like above in an answer on cstheory site but the basic idea is similar to the approach with independent sets -- fix some variables and recurse on subparts.
This kind of general factorization has been re-invented many times and is known as Generalized Distributive Law, tree-decomposition, junction tree, clique tree, partial k-tree, and probably a few other names.
Notebook
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