Titlebook: Making the History of Computing Relevant; IFIP WG 9.7 Internat Arthur Tatnall,Tilly Blyth,Roger Johnson Conference proceedings 2013 IFIP Fe

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Enliven

the proposed method is compared to an existing constraint-based method (RFCI) using data generated from several previously published Bayesian networks. The structural Hamming distances of the output models improved when using the proposed method compared to RFCI, especially for small sample sizes.

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鞠躬

Herbert Bruderer idea to the nonparametric version of LDA, hierarchical Dirichlet process topic models. Our fast sampling method leads to a significant speedup of variational updates as compared to other sampling methods. Experiments show that training of our topic model converges to a better log-likelihood than pr

cavity

A. Barbara Ainsworth,C. Avram,J. Sheard the proposed method is compared to an existing constraint-based method (RFCI) using data generated from several previously published Bayesian networks. The structural Hamming distances of the output models improved when using the proposed method compared to RFCI, especially for small sample sizes.

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the proposed method is compared to an existing constraint-based method (RFCI) using data generated from several previously published Bayesian networks. The structural Hamming distances of the output models improved when using the proposed method compared to RFCI, especially for small sample sizes.

辩论的终结

Giovanni A. Cignoni,Fabio Gadducciround 11 K images containing faces. An analysis of the captions finds that, perhaps surprisingly, the improvement in caption quality appears to come not from the addition of adjectives linked to emotional aspects of the images, but from more variety in the actions described in the captions. Code rel

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Chris Monkt in our sensor placement algorithm. . Our sensor placement algorithm is provably near-optimal, and both our algorithms outperform existing approaches in accuracy by . or more (F-measure) in experiments. . our algorithms scale ., and our detection algorithm is ., requiring bounded space and constant

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