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Stochastic Inference for Scalable Probabilistic Modeling of Binary Matrices.

J. Hernández-Lobato, N. Houlsby, and Z. Ghahramani. ICML, volume 32 of JMLR Workshop and Conference Proceedings, page 379-387. JMLR.org, (2014)

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Other publications of authors with the same name

A Comparison of Human and Agent Reinforcement Learning in Partially Observable Domains.F. Doshi-Velez, and Z. Ghahramani. CogSci, cognitivesciencesociety.org, (2011)Semi-Supervised Learning Using Gaussian Fields and Harmonic Functions.X. Zhu, Z. Ghahramani, and J. Lafferty. ICML, page 912-919. AAAI Press, (2003)Gaussian Process Volatility Model.Y. Wu, J. Hernández-Lobato, and Z. Ghahramani. NIPS, page 1044-1052. (2014)The Infinite Hidden Markov Model.M. Beal, Z. Ghahramani, and C. Rasmussen. NIPS, page 577-584. MIT Press, (2001)Collaborative Gaussian Processes for Preference Learning.N. Houlsby, J. Hernández-Lobato, F. Huszar, and Z. Ghahramani. NIPS, page 2105-2113. (2012)Learning to Parse Images.G. Hinton, Z. Ghahramani, and Y. Teh. NIPS, page 463-469. The MIT Press, (1999)The Mondrian Kernel.M. Balog, B. Lakshminarayanan, Z. Ghahramani, D. Roy, and Y. Teh. UAI, AUAI Press, (2016)MCMC for Doubly-intractable Distributions.I. Murray, Z. Ghahramani, and D. MacKay. UAI, AUAI Press, (2006)Spectral Methods for Automatic Multiscale Data Clustering.A. Azran, and Z. Ghahramani. CVPR (1), page 190-197. IEEE Computer Society, (2006)SMEM Algorithm for Mixture Models.N. Ueda, R. Nakano, Z. Ghahramani, and G. Hinton. Neural Computation, 12 (9): 2109-2128 (2000)

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Stochastic Inference for Scalable Probabilistic Modeling of Binary Matrices.

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copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Stochastic Inference for Scalable Probabilistic Modeling of Binary Matrices.

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Stochastic Inference for Scalable Probabilistic Modeling of Binary Matrices.