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This is one of the class meetings on the [[Syllabus for Machine Learning with Large Datasets 10-605 in Fall 2016|schedule]] for the course [[Machine Learning with Large Datasets 10-605 in Fall 2016]]. === Slides === * TBD === Readings === * [http://people.cs.umass.edu/~mimno/papers/fast-topic-model.pdf Efficient Methods for Topic Model Inference on Streaming Document Collections], Yao, Mimno, McCallum KDD 2009. * [http://dl.acm.org/citation.cfm?id=2623756 Reducing the sampling complexity of topic models], Li, Ahmed, Ravi, & Smola, KDD 2014 * [http://arxiv.org/abs/1412.1576 LightLDA: Big Topic Models on Modest Compute Clusters], Jinhui Yuan, Fei Gao, Qirong Ho, Wei Dai, Jinliang Wei, Xun Zheng, Eric P. Xing, Tie-Yan Liu, Wei-Ying Ma, 2015 === Things to Remember === * Why efficient sampling is important for LDAs * How sampling can be sped up for many topics by preprocessing the parameters of the distribution * How the storage used for LDA can be reduced by exploiting the fact that many words are rare.

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