As described in my AIMag article last year, SPI (symbolic
probabilistic inference) treats individual marginals as just a special
case of the general optimization problem of finding efficient ways to
compute arbitrary subjoints, and does a surprisingly good job at
arbitrary subnjoints. Variable elimination should work also.
The open research problem that no-one is working on (to my knowledge)
is to find efficient ways of computing an arbitrary collection of arbitrary
subjoints. No existing method seems to provide an interesting
starting point for that problem.
cheers - Bruce
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