Exact Structure Discovery in Bayesian Networks with Less Space
Pekka Parviainen, Mikko Koivisto
Abstract:
The fastest known exact algorithms for scorebased structure discovery in Bayesian networks on n nodes run in time and space 2nnO(1). The usage of these algorithms is limited to networks on at most around 25 nodes mainly due to the space requirement. Here, we study spacetime tradeoffs for finding an optimal network structure. When little space is available, we apply the GurevichShelah recurrenceoriginally proposed for the Hamiltonian path problemand obtain time 22nsnO(1) in space 2snO(1) for any s = n/2, n/4, n/8, . . .; we assume the indegree of each node is bounded by a constant. For the more practical setting with moderate amounts of space, we present a novel scheme. It yields running time 2n(3/2)pnO(1) in space 2n(3/4)pnO(1) for any p = 0, 1, . . . , n/2; these bounds hold as long as the indegrees are at most 0.238n. Furthermore, the latter scheme allows easy and efficient parallelization beyond previous algorithms. We also explore empirically the potential of the presented techniques.
Keywords: null
Pages: 436443
PS Link:
PDF Link: /papers/09/p436parviainen.pdf
BibTex:
@INPROCEEDINGS{Parviainen09,
AUTHOR = "Pekka Parviainen
and Mikko Koivisto",
TITLE = "Exact Structure Discovery in Bayesian Networks with Less Space",
BOOKTITLE = "Proceedings of the TwentyFifth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI09)",
PUBLISHER = "AUAI Press",
ADDRESS = "Corvallis, Oregon",
YEAR = "2009",
PAGES = "436443"
}

