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Probabilistic Topic Models., , and . IEEE Signal Process. Mag., 27 (6): 55-65 (2010)Mixed membership stochastic block models, , , and . Advances in Neural Information Processing Systems (NIPS) 21, Red Hook, NY: Curran Associates, (2009)Mixed membership stochastic block models for relational data, with applications to protein-protein interactions, , , and . Proceedings of International Biometric Society-ENAR Annual Meetings, (2006)Variational methods for the Dirichlet process., and . ICML, volume 69 of ACM International Conference Proceeding Series, ACM, (2004)Panel Discussion.. SNA@ICML, volume 4503 of Lecture Notes in Computer Science, page 186-194. Springer, (2006)Using Text Embeddings for Causal Inference., , and . CoRR, (2019)Stick-Breaking Beta Processes and the Poisson Process., , and . AISTATS, volume 22 of JMLR Proceedings, page 850-858. JMLR.org, (2012)Online Variational Inference for the Hierarchical Dirichlet Process., , and . AISTATS, volume 15 of JMLR Proceedings, page 752-760. JMLR.org, (2011)The Inverse Regression Topic Model., and . ICML, volume 32 of JMLR Workshop and Conference Proceedings, page 199-207. JMLR.org, (2014)Variational Inference: A Review for Statisticians, , and . (2016)cite arxiv:1601.00670.