PLDA+: Parallel latent dirichlet allocation with data placement and pipeline processing

PLDA+: Parallel latent dirichlet allocation with data placement and pipeline processing

PLDA+: Parallel Latent Dirichlet Allocation with Data Placement and Pipeline Processing ZHIYUAN L...概要を表示 PLDA+: Parallel Latent Dirichlet Allocation with Data Placement and Pipeline Processing ZHIYUAN LIU, YUZHOU ZHANG, and EDWARD Y. CHANG, Google Inc. MAOSONG SUN, Tsinghua University Previous methods of distributed Gibbs sampling for LDA run into either memory or communication bottlenecks. To improve scalability, we propose four strategies: data placement, pipeline processing, word bundling, and p

• LDA
• paper