Papers with SUB-LDA

1 papers
Improving Privacy Guarantee and Efficiency of Latent Dirichlet Allocation Model Training Under Differential Privacy (2021.findings-emnlp)

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Challenge: Latent Dirichlet allocation (LDA) is a widely used topic model to discover the latent semantic of text data.
Approach: They propose to combine a subsampling method with CGS to improve efficiency while amplifying privacy by using a novel metric, the efficiency–privacy function.
Outcome: The proposed algorithm improves efficiency while amplifying privacy while subsampling in CGS increases efficiency while preserving privacy.

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