Efficient Training of LDA on a GPU by Mean-for-Mode Estimation

    International Conference on Machine Learning, 2015.

    Cited by: 11|Bibtex|Views6|Links
    EI

    Abstract:

    We introduce Mean-for-Mode estimation, a variant of an uncollapsed Gibbs sampler that we use to train LDA on a GPU. The algorithm combines benefits of both uncollapsed and collapsed Gibbs samplers. Like a collapsed Gibbs sampler--and unlike an uncollapsed Gibbs sampler--it has good statistical performance, and can use sampling complexity ...More

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