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We develop stochastic variational inference, a scalable algorithm for approximating posterior distributions.
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Learning using large datasets
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An HDP-HMM for systems with state persistence
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A variational Bayesian framework for graphical models
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Variational inference for Bayesian mixtures of factor analysers
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Markov chain sampling methods for Dirichlet process mixture models
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Variational approximations between mean field theory and the junction tree algorithm
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An introduction to sequential Monte Carlo methods
A. Doucet, N. De Freitas, and N. Gordon · 2001
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Propagation algorithms for variational Bayesian learning
Z. Ghahramani and M. Beal · 2001
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Graphical models, exponential families, and variational inference
M. Wainwright and M. Jordan · 2008
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Continuous time dynamic topic models
C. Wang, D. Blei, and D. Heckerman · 2008
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On smoothing and inference for topic models
A. Asuncion, M. Welling, P. Smyth, and Y. Teh · 2009
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On-line expectation-maximization algorithm for latent data models
Olivier Cappé and Eric Moulines · 2009
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Probabilistic Graphical Models: Principles and Techniques
D. Koller and N. Friedman · 2009
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Distributed algorithms for topic models
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Nonparametric factor analysis with beta process priors
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Bayesian Nonparametrics
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Online learning for matrix factorization and sparse coding
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An architecture for parallel topic models
A. Smola and S. Narayanamurthy · 2010
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Non-conjugate variational message passing for multinomial and binary regression
D. Knowles and T. Minka · 2011
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Larger residuals, less work: Active document scheduling for latent dirichlet allocation
M. Wahabzada and K. Kersting · 2011
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Online variational inference for the hierarchical Dirichlet process
C. Wang, J. Paisley, and D. Blei · 2011
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Bayesian learning via stochastic gradient Langevin dynamics
M. Welling and Y. Teh · 2011
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Scalable inference in latent variable models
A. Ahmed, M. Aly, J. Gonzalez, S. Narayanamurthy, and A. Smola · 2012
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Probabilistic topic models
D. Blei · 2012
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A tutorial on Bayesian nonparametric models
S. Gershman and D. Blei · 2012
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Nonparametric variational inference
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Scalable inference of overlapping communities
P. Gopalan, D. Mimno, S. Gerrish, M. Freedman, and D. Blei · 2012
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Sparse stochastic inference for latent Dirichlet allocation
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Machine Learning: A Probabilistic Approach
K. Murphy · 2012
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An adaptive learning rate for stochastic variational inference
R. Ranganath, C. Wang, D. Blei, and E. Xing · 2013
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Variational inference in nonconjugate models
C. Wang and D. Blei · 2013
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