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Description
LightLDA: Big Topic Models on Modest Compute Clusters
- Current implementations of LDA ( Latent Dirichlet Allocation ) such as SparseLDA or AliasLDA allow to achieve massive data and model scales, for example models with tens of billions of parameters to be inferred from billions of documents. However this requires using cluster up to thousands of machines with all ensuing costs to setup and maintain.
- LightLDA solves this problem in a more cost-effective manner by providing an implementation that is efficient enough for modest clusters with at most tens of machines...
For more details please see LightLDA paper:
http://arxiv.org/abs/1412.1576
http://www.www2015.it/documents/proceedings/proceedings/p1351.pdf
and open source implementation:
https://github.com/Microsoft/LightLDA