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Neural Information Processing Systems 

First provide a summary of the paper, and then address the following criteria: Quality, clarity, originality and significance. The authors describe a two novel inference methods for the correlated topic model (CTM). They build on analytic results for the conditional logistic normal likelihood to arrive at a fast, easily parallelized exact inference. This leads to an approximate sampling method for producing Polya-Gamma variates. Finally, they propose a method for efficiently drawing samples in the presence of sparsity.