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More influence means less work: fast latent dirichlet allocation by influence scheduling

Mirwaes Wahabzada; Kristian Kersting; Anja Pilz; Christian Bauckhage
In: Craig Macdonald; Iadh Ounis; Ian Ruthven (Hrsg.). Proceedings of the 20th ACM Conference on Information and Knowledge Management. ACM International Conference on Information and Knowledge Management (CIKM-2011), October 24-28, Glasgow, United Kingdom, Pages 2273-2276, ACM, 2011.


There have recently been considerable advances in fast inference for (online) latent Dirichlet allocation (LDA). While it is widely recognized that the scheduling of documents in stochastic optimization and in turn in LDA may have significant consequences, this issue remains largely unexplored. Instead, practitioners schedule documents essentially uniformly at random, due perhaps to ease of implementation, and to the lack of clear guidelines on scheduling the documents.

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