Guoqiang Li

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This paper presents our recent efforts, ZenLDA, an efficient and scalable Collapsed Gibbs Sampling (CGS) system for Latent Dirichlet Allocation (LDA) training, which is thought to be challenging that both data parallelism and model parallelism are required because of the Big sampling data with up to billions of documents and Big model size with up to(More)
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