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Techniques for compressing a large distributed empirical sample of a compound probability distribution into an approximate parametric distribution with scalable parallel processing
Techniques for compressing a large distributed empirical sample of a compound probability distribution into an approximate parametric distribution with scalable parallel processing
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机译：利用可伸缩并行处理将复合概率分布的大型分布式经验样本压缩为近似参数分布的技术
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摘要
Techniques for estimated compound probability distribution are described. An apparatus may comprise a configuration component, perturbation component, sample generation controller, an aggregation component, a distribution fitting component, and statistics generation component. The configuration component may be operative to receive a compound model specification and candidate distribution definition. The perturbation component may be operative to generate a plurality of models from the compound model specification. The sample generation controller may be operative to initiate the generation of a plurality of compound model samples from each of the plurality of models. The distribution fitting component may generate parameter values for the candidate distribution definition based on the compound model samples. The statistics generation component may generate approximated aggregate statistics. Other embodiments are described and claimed.
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