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نویسندگان
چکیده
منابع مشابه
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We propose to compress Bayesian networks (BNs), reducing the space complexity to being fully linear, in order to widely deploy in low-resource platforms, such as smart mobile devices. We present a novel method that compresses each conditional probability table (CPT) of an arbitrary binary BN into a Non-impeding noisy-And Tree (NAT) model. It achieves the above goal in the binary case. Experimen...
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TABLE 1 Fitted parameters determined from two-component decomposition of the light profiles.
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To specify a Bayes net (BN), a conditional probability table (CPT), often of an effect conditioned on its n causes, needs assessed for each node. It generally has the complexity exponential on n. Noisy-OR reduces the complexity to linear, but can only represent reinforcing causal interactions. The non-impeding noisy-AND (NIN-AND) tree is the first causal model that explicitly expresses reinforc...
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To specify a Bayes net, a conditional probability table, often of an effect conditioned on its n causes, needs to be assessed for each node. Its complexity is generally exponential in n and hence how to scale up is important to knowledge engineering. The non-impeding noisy-AND (NIN-AND) tree causal model reduces the complexity to linear while explicitly expressing both reinforcing and undermini...
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ژورنال
عنوان ژورنال: History Studies International Journal of History
سال: 2018
ISSN: 1309-4688
DOI: 10.9737/hist.2018.623