Variational Inference: A Review for Statisticians

One of the core problems of modern statistics is to approximate difficult-to-compute probability densities. This problem is especially important in Bayesian statistics, which frames all inference about unknown quantities as a calculation involving the posterior density. In this article, we review va...

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Vydáno v:	Journal of the American Statistical Association Ročník 112; číslo 518; s. 859 - 877
Hlavní autoři:	Blei, David M., Kucukelbir, Alp, McAuliffe, Jon D.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Alexandria Taylor & Francis 03.04.2017 Taylor & Francis Group,LLC Taylor & Francis Ltd
Témata:	Algorithms Americans artificial intelligence Bayesian analysis Bayesian theory catalytic activity Closeness Computationally intensive methods Density Families & family life Inference Machine learning Markov analysis Markov chain Markov chains mixtures Optimization Probability probability distribution Review Sampling Scholarship Statistical analysis Statistical computing Statistical inference Statistics
ISSN:	0162-1459, 1537-274X, 1537-274X
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Abstract	One of the core problems of modern statistics is to approximate difficult-to-compute probability densities. This problem is especially important in Bayesian statistics, which frames all inference about unknown quantities as a calculation involving the posterior density. In this article, we review variational inference (VI), a method from machine learning that approximates probability densities through optimization. VI has been used in many applications and tends to be faster than classical methods, such as Markov chain Monte Carlo sampling. The idea behind VI is to first posit a family of densities and then to find a member of that family which is close to the target density. Closeness is measured by Kullback-Leibler divergence. We review the ideas behind mean-field variational inference, discuss the special case of VI applied to exponential family models, present a full example with a Bayesian mixture of Gaussians, and derive a variant that uses stochastic optimization to scale up to massive data. We discuss modern research in VI and highlight important open problems. VI is powerful, but it is not yet well understood. Our hope in writing this article is to catalyze statistical research on this class of algorithms. Supplementary materials for this article are available online.
AbstractList	One of the core problems of modern statistics is to approximate difficult-to-compute probability densities. This problem is especially important in Bayesian statistics, which frames all inference about unknown quantities as a calculation involving the posterior density. In this article, we review variational inference (VI), a method from machine learning that approximates probability densities through optimization. VI has been used in many applications and tends to be faster than classical methods, such as Markov chain Monte Carlo sampling. The idea behind VI is to first posit a family of densities and then to find a member of that family which is close to the target density. Closeness is measured by Kullback–Leibler divergence. We review the ideas behind mean-field variational inference, discuss the special case of VI applied to exponential family models, present a full example with a Bayesian mixture of Gaussians, and derive a variant that uses stochastic optimization to scale up to massive data. We discuss modern research in VI and highlight important open problems. VI is powerful, but it is not yet well understood. Our hope in writing this article is to catalyze statistical research on this class of algorithms. Supplementary materials for this article are available online. One of the core problems of modern statistics is to approximate difficult-to-compute probability densities. This problem is especially important in Bayesian statistics, which frames all inference about unknown quantities as a calculation involving the posterior density. In this article, we review variational inference (VI), a method from machine learning that approximates probability densities through optimization. VI has been used in many applications and tends to be faster than classical methods, such as Markov chain Monte Carlo sampling. The idea behind VI is to first posit a family of densities and then to find a member of that family which is close to the target density. Closeness is measured by Kullback-Leibler divergence. We review the ideas behind mean-field variational inference, discuss the special case of VI applied to exponential family models, present a full example with a Bayesian mixture of Gaussians, and derive a variant that uses stochastic optimization to scale up to massive data. We discuss modern research in VI and highlight important open problems. VI is powerful, but it is not yet well understood. Our hope in writing this article is to catalyze statistical research on this class of algorithms.
Author	Blei, David M. Kucukelbir, Alp McAuliffe, Jon D.
Author_xml	– sequence: 1 givenname: David M. surname: Blei fullname: Blei, David M. organization: Department of Computer Science and Statistics, Columbia University – sequence: 2 givenname: Alp surname: Kucukelbir fullname: Kucukelbir, Alp email: alp@cs.columbia.edu organization: Department of Computer Science, Columbia University – sequence: 3 givenname: Jon D. surname: McAuliffe fullname: McAuliffe, Jon D. organization: Department of Statistics, University of California
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Cites_doi	10.1162/tacl_a_00175 10.1016/j.jtbi.2003.07.002 10.1214/aoms/1177729586 10.1016/j.neuroimage.2006.10.005 10.1109/TSP.2004.831119 10.1109/TPAMI.2009.110 10.1016/j.neuroimage.2007.04.054 10.1371/journal.pcbi.1000770 10.1214/13-AOS1124 10.1063/1.1699114 10.1162/jmlr.2003.3.4-5.993 10.1561/2200000001 10.1111/biom.12126 10.1534/genetics.114.164350 10.1093/pan/mpq027 10.1214/07-AOAS126 10.1214/11-AOS908 10.1371/journal.pone.0094914 10.1109/TBME.2004.824128 10.1214/06-BA104 10.1198/jasa.2009.tm08030 10.1080/01621459.1990.10476213 10.1109/TPAMI.2009.43 10.1007/978-1-4419-9017-4_6 10.1093/bioinformatics/btl473 10.1080/10618600.2012.679897 10.1145/2133806.2133826 10.1016/j.neuroimage.2011.08.031 10.1016/j.neuroimage.2014.04.055 10.1103/PhysRevLett.100.258701 10.1613/jair.251 10.1109/TPAMI.1984.4767596 10.1177/0278364908090961 10.1023/A:1007665907178 10.1016/j.neuroimage.2009.12.042 10.1214/aoms/1177729694 10.1080/10618600.2014.983642 10.1016/j.robot.2011.11.002 10.1214/13-STS418 10.1002/0471722138 10.1214/07-AOAS114 10.1111/j.2517-6161.1977.tb01600.x 10.1111/anzs.12063 10.1007/11872436_8 10.1007/s11222-017-9729-7 10.1007/978-3-540-69162-4_32 10.1016/j.neuroimage.2004.08.034 10.1145/2124295.2124312 10.1007/978-94-011-5014-9_12 10.1111/j.2517-6161.1988.tb01721.x 10.1016/j.csda.2006.07.020 10.1214/14-EJS910 10.1162/089976601750399344 10.1162/089976601750265045 10.1613/jair.2473 10.1093/biomet/57.1.97 10.1016/j.spl.2011.02.029 10.1214/aos/1176345779 10.1002/9780470316870 10.1214/12-BA703 10.1016/j.neuroimage.2003.12.023 10.1007/978-1-4757-4145-2 10.1023/A:1007425814087 10.1109/TSP.2002.801921 10.1017/CBO9780511804779 10.1371/journal.pcbi.1003441 10.1214/12-EJS729 10.1023/A:1008932416310 10.1016/j.neucom.2005.02.016 10.1016/j.neuroimage.2004.06.037 10.1016/S1053-8119(03)00071-5 10.1214/06-BA121 10.1007/978-1-4899-2696-8 10.1214/11-BA631 10.1214/aos/1176344611 10.1016/j.neuroimage.2007.09.005 10.1109/TPAMI.2008.157 10.1162/089976698300017746 10.1016/j.neuroimage.2008.02.059 10.1093/bioinformatics/bth917 10.1186/1471-2105-11-58 10.1016/S0893-6080(02)00040-0 10.1613/jair.567 10.1142/S0219720004000508
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References	e_1_3_2_28_1 Armagan A. (e_1_3_2_8_1) 2011 Winn J. (e_1_3_2_160_1) 2005; 6 e_1_3_2_66_1 e_1_3_2_43_1 e_1_3_2_24_1 e_1_3_2_47_1 e_1_3_2_89_1 e_1_3_2_100_1 e_1_3_2_146_1 Brown L. (e_1_3_2_26_1) 1986 Hinton G. (e_1_3_2_58_1) 1993 e_1_3_2_142_1 e_1_3_2_81_1 e_1_3_2_123_1 e_1_3_2_165_1 Opper M. (e_1_3_2_102_1) 2005; 6 e_1_3_2_108_1 (e_1_3_2_65_1) 1997 e_1_3_2_16_1 e_1_3_2_39_1 Sudderth E. B. (e_1_3_2_132_1) 2009 Airoldi E. (e_1_3_2_3_1) 2008; 9 Wang C. (e_1_3_2_152_1) 2015; 14 e_1_3_2_31_1 e_1_3_2_54_1 e_1_3_2_77_1 Saul L. (e_1_3_2_127_1) 1996 e_1_3_2_161_1 e_1_3_2_92_1 Barber D. (e_1_3_2_12_1) 2006 e_1_3_2_135_1 e_1_3_2_158_1 e_1_3_2_73_1 e_1_3_2_131_1 Archambeau C. (e_1_3_2_6_1) 2007; 1 Barber D. (e_1_3_2_14_1) 1999 de Freitas N. D. (e_1_3_2_34_1) 2001 e_1_3_2_154_1 Dempster A. (e_1_3_2_37_1) 1977; 39 Beal M. (e_1_3_2_15_1) 2003 Titsias M. (e_1_3_2_139_1) 2010 Kingma D. (e_1_3_2_74_1) 2014 e_1_3_2_29_1 Salimans T. (e_1_3_2_122_1) 2015 Welling M. (e_1_3_2_156_1) 2011 Ranganath R. (e_1_3_2_113_1) 2016 e_1_3_2_21_1 e_1_3_2_63_1 Yu T. (e_1_3_2_167_1) 2005 e_1_3_2_25_1 e_1_3_2_48_1 e_1_3_2_67_1 Tran D. (e_1_3_2_141_1) 2016 Rezende D. J. (e_1_3_2_116_1) 2014 e_1_3_2_126_1 e_1_3_2_168_1 Stan Development Team (e_1_3_2_130_1) 2015 e_1_3_2_103_1 Hensman J. (e_1_3_2_56_1) 2013 Wang C. (e_1_3_2_151_1) 2013; 14 Hoffman M. D. (e_1_3_2_62_1) 2014; 15 Hoffman M. (e_1_3_2_59_1) 2012 e_1_3_2_107_1 Wang P. (e_1_3_2_153_1) 2013 Minka T. (e_1_3_2_96_1) 2014 Naseem T. (e_1_3_2_97_1) 2010 Vermaak J. (e_1_3_2_144_1) 2003 e_1_3_2_17_1 e_1_3_2_2_1 Barber D. (e_1_3_2_11_1) 1998 e_1_3_2_55_1 Jojic N. (e_1_3_2_69_1) 2001 Liang P. (e_1_3_2_86_1) 2007 Giordano R. J. (e_1_3_2_50_1) 2015 e_1_3_2_13_1 Reyes-Gomez M. (e_1_3_2_115_1) 2004 Waterhouse S. (e_1_3_2_155_1) 1996 e_1_3_2_36_1 e_1_3_2_78_1 e_1_3_2_93_1 e_1_3_2_138_1 e_1_3_2_157_1 e_1_3_2_51_1 e_1_3_2_111_1 e_1_3_2_134_1 e_1_3_2_70_1 Khan M. E. (e_1_3_2_72_1) 2010 Pearl J. (e_1_3_2_106_1) 1988 Bishop C. (e_1_3_2_20_1) 2000 Hall P. (e_1_3_2_52_1) 2011; 21 e_1_3_2_119_1 e_1_3_2_49_1 e_1_3_2_87_1 e_1_3_2_22_1 Ranganath R. (e_1_3_2_112_1) 2014 Yedidia J. S. (e_1_3_2_164_1) 2001 e_1_3_2_125_1 Hensman J. (e_1_3_2_57_1) 2012 e_1_3_2_148_1 Furmston T. (e_1_3_2_45_1) 2010; 9 e_1_3_2_121_1 Archambeau C. (e_1_3_2_7_1) 2007 e_1_3_2_129_1 Tan L. (e_1_3_2_136_1) 2014; 9 e_1_3_2_9_1 Kucukelbir A. (e_1_3_2_76_1) 2015 Parisi G. (e_1_3_2_105_1) 1988 Knowles D. (e_1_3_2_75_1) 2011 e_1_3_2_163_1 e_1_3_2_10_1 e_1_3_2_33_1 Hoffman M. D. (e_1_3_2_60_1) 2013; 14 e_1_3_2_5_1 Marlin B. M. (e_1_3_2_91_1) 2011 Peterson C. (e_1_3_2_109_1) 1987; 1 Du L. (e_1_3_2_40_1) 2009 e_1_3_2_79_1 e_1_3_2_98_1 Liang P. (e_1_3_2_85_1) 2009 Bishop C. (e_1_3_2_18_1) 2006 Titsias M. (e_1_3_2_140_1) 2014 e_1_3_2_137_1 Wang B. (e_1_3_2_149_1) 2005 e_1_3_2_110_1 Ermis B. (e_1_3_2_41_1) 2014 e_1_3_2_71_1 e_1_3_2_90_1 e_1_3_2_133_1 e_1_3_2_118_1 e_1_3_2_27_1 Cohen S. (e_1_3_2_32_1) 2010; 11 Villegas M. (e_1_3_2_145_1) 2013 e_1_3_2_42_1 e_1_3_2_88_1 Johnson M. (e_1_3_2_68_1) 2014 e_1_3_2_150_1 e_1_3_2_23_1 e_1_3_2_46_1 Regier J. (e_1_3_2_114_1) 2015 e_1_3_2_80_1 e_1_3_2_101_1 e_1_3_2_124_1 e_1_3_2_84_1 e_1_3_2_120_1 e_1_3_2_143_1 e_1_3_2_166_1 e_1_3_2_128_1 Damianou A. (e_1_3_2_35_1) 2011 e_1_3_2_38_1 Challis E. (e_1_3_2_30_1) 2013; 14 Le Cun Y. (e_1_3_2_83_1) 2004 e_1_3_2_162_1 Wand M. (e_1_3_2_147_1) 2014; 15 Paisley J. (e_1_3_2_104_1) 2012 e_1_3_2_53_1 Jaakkola T. (e_1_3_2_64_1) 1996 e_1_3_2_4_1 e_1_3_2_99_1 e_1_3_2_159_1 Bishop C. (e_1_3_2_19_1) 1998 Foti N. (e_1_3_2_44_1) 2014 e_1_3_2_95_1 Lauritzen S. (e_1_3_2_82_1) 1988; 50 Minka T. P. (e_1_3_2_94_1) 2001 Hoffman M. D. (e_1_3_2_61_1) 2015 e_1_3_2_117_1
References_xml	– start-page: 1234 year: 2010 ident: e_1_3_2_97_1 article-title: Using Universal Linguistic Knowledge to Guide Grammar Induction publication-title: Empirical Methods in Natural Language Processing – volume-title: Statistical Field Theory year: 1988 ident: e_1_3_2_105_1 – start-page: 416 year: 1998 ident: e_1_3_2_19_1 article-title: Approximating Posterior Distributions in Belief Networks using Mixtures publication-title: Neural Information Processing Systems – ident: e_1_3_2_165_1 doi: 10.1162/tacl_a_00175 – start-page: 192 year: 2014 ident: e_1_3_2_41_1 article-title: Iterative Splits of Quadratic Bounds for Scalable Binary Tensor Factorization publication-title: Uncertainty in Artificial Intelligence – ident: e_1_3_2_89_1 – start-page: 361 year: 2015 ident: e_1_3_2_61_1 article-title: Structured Stochastic Variational Inference publication-title: Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics (Vol. 38), eds. G. Lebanon and S. V. N. Vishwanathan, San Diego, CA: Proceedings of Machine Learning Research – ident: e_1_3_2_119_1 doi: 10.1016/j.jtbi.2003.07.002 – ident: e_1_3_2_117_1 doi: 10.1214/aoms/1177729586 – ident: e_1_3_2_43_1 doi: 10.1016/j.neuroimage.2006.10.005 – start-page: 776 volume-title: The Handbook of Applied Bayesian Analysis year: 2009 ident: e_1_3_2_85_1 – ident: e_1_3_2_121_1 – ident: e_1_3_2_87_1 doi: 10.1109/TSP.2004.831119 – ident: e_1_3_2_31_1 doi: 10.1109/TPAMI.2009.110 – ident: e_1_3_2_168_1 doi: 10.1016/j.neuroimage.2007.04.054 – start-page: 1108 year: 2010 ident: e_1_3_2_72_1 article-title: Variational Bounds for Mixed-Data Factor Analysis publication-title: Neural Information Processing Systems – ident: e_1_3_2_131_1 doi: 10.1371/journal.pcbi.1000770 – volume-title: Fundamentals of Statistical Exponential Families year: 1986 ident: e_1_3_2_26_1 – ident: e_1_3_2_17_1 doi: 10.1214/13-AOS1124 – ident: e_1_3_2_93_1 doi: 10.1063/1.1699114 – ident: e_1_3_2_24_1 doi: 10.1162/jmlr.2003.3.4-5.993 – ident: e_1_3_2_146_1 doi: 10.1561/2200000001 – ident: e_1_3_2_98_1 doi: 10.1111/biom.12126 – volume: 15 start-page: 1351 year: 2014 ident: e_1_3_2_147_1 article-title: Fully Simplified Multivariate Normal Updates in Non-Conjugate Variational Message Passing publication-title: Journal of Machine Learning Research – ident: e_1_3_2_110_1 doi: 10.1534/genetics.114.164350 – ident: e_1_3_2_51_1 doi: 10.1093/pan/mpq027 – start-page: 486 year: 2009 ident: e_1_3_2_40_1 article-title: A Bayesian Model for Simultaneous Image Clustering, Annotation and Object Segmentation publication-title: Neural Information Processing Systems – ident: e_1_3_2_42_1 doi: 10.1214/07-AOAS126 – ident: e_1_3_2_53_1 doi: 10.1214/11-AOS908 – ident: e_1_3_2_90_1 doi: 10.1371/journal.pone.0094914 – start-page: 453 volume-title: Bayesian Statistics year: 2003 ident: e_1_3_2_15_1 – ident: e_1_3_2_134_1 doi: 10.1109/TBME.2004.824128 – volume: 6 start-page: 2177 year: 2005 ident: e_1_3_2_102_1 article-title: Expectation Consistent Approximate Inference publication-title: The Journal of Machine Learning Research – ident: e_1_3_2_22_1 doi: 10.1214/06-BA104 – ident: e_1_3_2_25_1 doi: 10.1198/jasa.2009.tm08030 – ident: e_1_3_2_46_1 doi: 10.1080/01621459.1990.10476213 – start-page: 1599 year: 2012 ident: e_1_3_2_59_1 article-title: Sparse Stochastic Inference for Latent Dirichlet Allocation publication-title: Proceedings of the 29th International Conference on Machine Learning (ICML-12), eds. J. Langford and J. Pineau, New York: ACM – ident: e_1_3_2_154_1 doi: 10.1109/TPAMI.2009.43 – ident: e_1_3_2_38_1 doi: 10.1007/978-1-4419-9017-4_6 – ident: e_1_3_2_124_1 doi: 10.1093/bioinformatics/btl473 – year: 2014 ident: e_1_3_2_74_1 article-title: Auto-Encoding Variational Bayes publication-title: Proceedings of the 2nd International Conference on Learning Representations (ICLR) – ident: e_1_3_2_101_1 doi: 10.1080/10618600.2012.679897 – start-page: 1585 year: 2009 ident: e_1_3_2_132_1 article-title: Shared Segmentation of Natural Scenes using Dependent Pitman-Yor Processes publication-title: Neural Information Processing Systems – ident: e_1_3_2_21_1 doi: 10.1145/2133806.2133826 – volume: 1 start-page: 1 year: 2007 ident: e_1_3_2_6_1 article-title: Gaussian Process Approximations of Stochastic Differential Equations publication-title: Workshop on Gaussian Processes in Practice – volume: 11 start-page: 3017 year: 2010 ident: e_1_3_2_32_1 article-title: Covariance in Unsupervised Learning of Probabilistic Grammars publication-title: The Journal of Machine Learning Research – ident: e_1_3_2_81_1 doi: 10.1016/j.neuroimage.2011.08.031 – start-page: 183 year: 1999 ident: e_1_3_2_14_1 article-title: Tractable Variational Structures for Approximating Graphical Models publication-title: Neural Information Processing Systems – ident: e_1_3_2_48_1 doi: 10.1016/j.neuroimage.2014.04.055 – ident: e_1_3_2_158_1 doi: 10.1103/PhysRevLett.100.258701 – start-page: 215 volume-title: Generalization in Neural Networks and Machine Learning year: 1998 ident: e_1_3_2_11_1 – ident: e_1_3_2_128_1 doi: 10.1613/jair.251 – start-page: 939 year: 2005 ident: e_1_3_2_167_1 article-title: Decentralized Multiple Target Tracking using Netted Collaborative Autonomous Trackers publication-title: Computer Vision and Pattern Recognition – ident: e_1_3_2_47_1 doi: 10.1109/TPAMI.1984.4767596 – start-page: 340 year: 1996 ident: e_1_3_2_64_1 article-title: Computing Upper and Lower Bounds on Likelihoods in Intractable Networks publication-title: Uncertainty in Artificial Intelligence – start-page: 373 year: 2005 ident: e_1_3_2_149_1 article-title: Inadequacy of Interval Estimates Corresponding to Variational Bayesian Approximations publication-title: Artificial Intelligence and Statistics – ident: e_1_3_2_103_1 – ident: e_1_3_2_33_1 doi: 10.1177/0278364908090961 – start-page: 1701 year: 2011 ident: e_1_3_2_75_1 article-title: Non-Conjugate Variational Message Passing for Multinomial and Binary Regression publication-title: Neural Information Processing Systems – start-page: 523 year: 2011 ident: e_1_3_2_8_1 article-title: Generalized Beta Mixtures of Gaussians publication-title: Neural Information Processing Systems – ident: e_1_3_2_71_1 doi: 10.1023/A:1007665907178 – volume-title: Pattern Recognition and Machine Learning year: 2006 ident: e_1_3_2_18_1 – start-page: 362 year: 2001 ident: e_1_3_2_94_1 article-title: Expectation Propagation for Approximate Bayesian Inference publication-title: Uncertainty in Artificial Intelligence – ident: e_1_3_2_54_1 doi: 10.1016/j.neuroimage.2009.12.042 – ident: e_1_3_2_78_1 doi: 10.1214/aoms/1177729694 – start-page: 1 year: 2016 ident: e_1_3_2_141_1 article-title: The Variational Gaussian Process publication-title: International Conference on Learning Representations – start-page: 681 year: 2011 ident: e_1_3_2_156_1 article-title: Bayesian Learning via Stochastic Gradient Langevin Dynamics publication-title: International Conference on Machine Learning – ident: e_1_3_2_27_1 doi: 10.1080/10618600.2014.983642 – start-page: 120 year: 2001 ident: e_1_3_2_34_1 article-title: Variational MCMC publication-title: Uncertainty in Artificial Intelligence – start-page: 3599 year: 2014 ident: e_1_3_2_44_1 article-title: Stochastic Variational Inference for Hidden Markov Models publication-title: Neural Information Processing Systems – volume: 14 start-page: 1005 year: 2015 ident: e_1_3_2_152_1 article-title: A General Method for Robust Bayesian Modeling publication-title: Journal of Machine Learning Research – ident: e_1_3_2_111_1 doi: 10.1016/j.robot.2011.11.002 – ident: e_1_3_2_135_1 doi: 10.1214/13-STS418 – ident: e_1_3_2_129_1 doi: 10.1002/0471722138 – ident: e_1_3_2_23_1 doi: 10.1214/07-AOAS114 – year: 2014 ident: e_1_3_2_96_1 publication-title: Infer.NET 2.6. Cambridge, MA: Microsoft Research. – volume: 9 start-page: 241 year: 2010 ident: e_1_3_2_45_1 article-title: Variational Methods for Reinforcement Learning publication-title: Artificial Intelligence and Statistics – volume: 39 start-page: 1 year: 1977 ident: e_1_3_2_37_1 article-title: Maximum Likelihood from Incomplete Data via the EM Algorithm publication-title: Journal of the Royal Statistical Society doi: 10.1111/j.2517-6161.1977.tb01600.x – ident: e_1_3_2_166_1 doi: 10.1111/anzs.12063 – start-page: 1 year: 1997 ident: e_1_3_2_65_1 article-title: A Variational Approach to Bayesian Logistic Regression Models and their Extensions publication-title: Artificial Intelligence and Statistics – volume: 14 start-page: 1005 year: 2013 ident: e_1_3_2_151_1 article-title: Variational Inference in Nonconjugate Models publication-title: Journal of Machine Learning Research – volume: 15 start-page: 1593 year: 2014 ident: e_1_3_2_62_1 article-title: The No-U-turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo publication-title: The Journal of Machine Learning Research – start-page: 81 year: 2006 ident: e_1_3_2_12_1 article-title: Unified Inference for Variational Bayesian Linear Gaussian State-Space Models publication-title: Neural Information Processing Systems – start-page: 689 year: 2001 ident: e_1_3_2_164_1 article-title: Generalized Belief Propagation publication-title: Neural Information Processing Systems – ident: e_1_3_2_95_1 – ident: e_1_3_2_79_1 doi: 10.1007/11872436_8 – ident: e_1_3_2_67_1 – start-page: 5 year: 1993 ident: e_1_3_2_58_1 article-title: Keeping the Neural Networks Simple by Minimizing the Description Length of the Weights publication-title: Computational Learning Theory – ident: e_1_3_2_137_1 doi: 10.1007/s11222-017-9729-7 – ident: e_1_3_2_63_1 doi: 10.1007/978-3-540-69162-4_32 – ident: e_1_3_2_108_1 doi: 10.1016/j.neuroimage.2004.08.034 – start-page: 1 year: 2003 ident: e_1_3_2_144_1 article-title: Variational Inference for Visual Tracking publication-title: Computer Vision and Pattern Recognition – ident: e_1_3_2_2_1 doi: 10.1145/2124295.2124312 – start-page: 486 year: 1996 ident: e_1_3_2_127_1 article-title: Exploiting Tractable Substructures in Intractable Networks publication-title: Neural Information Processing Systems – ident: e_1_3_2_159_1 – start-page: 688 year: 2007 ident: e_1_3_2_86_1 article-title: The Infinite PCFG using Hierarchical Dirichlet Processes publication-title: Empirical Methods in Natural Language Processing – start-page: 1218 year: 2015 ident: e_1_3_2_122_1 article-title: Markov Chain Monte Carlo and Variational Inference: Bridging the Gap publication-title: International Conference on Machine Learning – ident: e_1_3_2_99_1 doi: 10.1007/978-94-011-5014-9_12 – volume-title: Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference year: 1988 ident: e_1_3_2_106_1 – volume: 50 start-page: 157 year: 1988 ident: e_1_3_2_82_1 article-title: Local Computations with Probabilities on Graphical Structures and their Application to Expert Systems publication-title: Journal of the Royal Statistical Society doi: 10.1111/j.2517-6161.1988.tb01721.x – start-page: 217 year: 2004 ident: e_1_3_2_83_1 article-title: Large Scale Online Learning publication-title: Neural Information Processing Systems – start-page: 308 year: 2013 ident: e_1_3_2_145_1 article-title: Overview of the ImageCLEF 2013 Scalable Concept Image Annotation Subtask publication-title: CLEF Evaluation Labs and Workshop – start-page: 1854 year: 2014 ident: e_1_3_2_68_1 article-title: Stochastic Variational Inference for Bayesian Time Series Models publication-title: International Conference on Machine Learning – ident: e_1_3_2_92_1 doi: 10.1016/j.csda.2006.07.020 – ident: e_1_3_2_100_1 doi: 10.1214/14-EJS910 – volume: 1 start-page: 995 year: 1987 ident: e_1_3_2_109_1 article-title: A Mean Field Theory Learning Algorithm for Neural Networks publication-title: Complex Systems – volume: 6 start-page: 661 year: 2005 ident: e_1_3_2_160_1 article-title: Variational Message Passing publication-title: Journal of Machine Learning Research – ident: e_1_3_2_157_1 – volume: 14 start-page: 1303 year: 2013 ident: e_1_3_2_60_1 article-title: Stochastic Variational Inference publication-title: Journal of Machine Learning Research – ident: e_1_3_2_84_1 doi: 10.1162/089976601750399344 – ident: e_1_3_2_125_1 doi: 10.1162/089976601750265045 – ident: e_1_3_2_143_1 doi: 10.1613/jair.2473 – ident: e_1_3_2_55_1 doi: 10.1093/biomet/57.1.97 – start-page: 282 year: 2013 ident: e_1_3_2_56_1 article-title: Gaussian Processes for Big Data publication-title: Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence – volume: 9 start-page: 963 year: 2014 ident: e_1_3_2_136_1 article-title: A Stochastic Variational Framework for Fitting and Diagnosing Generalized Linear Mixed Models publication-title: Bayesian Analysis – volume: 9 start-page: 1981 year: 2008 ident: e_1_3_2_3_1 article-title: Mixed Membership Stochastic Blockmodels publication-title: Journal of Machine Learning Research – ident: e_1_3_2_9_1 doi: 10.1016/j.spl.2011.02.029 – ident: e_1_3_2_4_1 doi: 10.1214/aos/1176345779 – ident: e_1_3_2_16_1 doi: 10.1002/9780470316870 – start-page: 2510 year: 2011 ident: e_1_3_2_35_1 article-title: Variational Gaussian Process Dynamical Systems publication-title: Neural Information Processing Systems – ident: e_1_3_2_28_1 doi: 10.1214/12-BA703 – ident: e_1_3_2_162_1 doi: 10.1016/j.neuroimage.2003.12.023 – ident: e_1_3_2_118_1 doi: 10.1007/978-1-4757-4145-2 – start-page: 1971 year: 2014 ident: e_1_3_2_140_1 article-title: Doubly Stochastic Variational Bayes for Non-Conjugate Inference publication-title: International Conference on Machine Learning – ident: e_1_3_2_49_1 doi: 10.1023/A:1007425814087 – start-page: 633 year: 2011 ident: e_1_3_2_91_1 article-title: Piecewise Bounds for Estimating Bernoulli-Logistic Latent Gaussian Models publication-title: International Conference on Machine Learning – start-page: 1278 year: 2014 ident: e_1_3_2_116_1 article-title: Stochastic Backpropagation and Approximate Inference in Deep Generative Models publication-title: Proceedings of the 31st International Conference on Machine Learning (Vol. 32), eds. E. P. Xing and T. Jebara, Beijing, China: Proceedings of Machine Learning Research – ident: e_1_3_2_120_1 doi: 10.1109/TSP.2002.801921 – ident: e_1_3_2_10_1 doi: 10.1017/CBO9780511804779 – ident: e_1_3_2_36_1 doi: 10.1371/journal.pcbi.1003441 – ident: e_1_3_2_29_1 doi: 10.1214/12-EJS729 – ident: e_1_3_2_66_1 doi: 10.1023/A:1008932416310 – ident: e_1_3_2_138_1 doi: 10.1016/j.neucom.2005.02.016 – start-page: 814 year: 2014 ident: e_1_3_2_112_1 article-title: Black Box Variational Inference publication-title: Artificial Intelligence and Statistics – ident: e_1_3_2_126_1 doi: 10.1016/j.neuroimage.2004.06.037 – ident: e_1_3_2_107_1 doi: 10.1016/S1053-8119(03)00071-5 – start-page: 641 year: 2004 ident: e_1_3_2_115_1 article-title: Multiband Audio Modeling for Single-Channel Acoustic Source Separation publication-title: Acoustics, Speech, and Signal Processing – ident: e_1_3_2_77_1 – ident: e_1_3_2_150_1 doi: 10.1214/06-BA121 – start-page: 351 year: 1996 ident: e_1_3_2_155_1 article-title: Bayesian Methods for Mixtures of Experts publication-title: Neural Information Processing Systems – start-page: 1363 year: 2012 ident: e_1_3_2_104_1 article-title: Variational Bayesian Inference with Stochastic Search publication-title: Proceedings of the 29th International Conference on International Conference on Machine Learning – start-page: 17 year: 2007 ident: e_1_3_2_7_1 article-title: Variational Inference for Diffusion Processes publication-title: Neural Information Processing Systems – start-page: 599 year: 2013 ident: e_1_3_2_153_1 article-title: Collapsed Variational Bayesian Inference for Hidden Markov Models publication-title: Artificial Intelligence and Statistics – start-page: 3 year: 2000 ident: e_1_3_2_20_1 article-title: Non-linear Bayesian Image Modelling publication-title: European Conference on Computer Vision – volume: 21 start-page: 369 year: 2011 ident: e_1_3_2_52_1 article-title: Theory of Gaussian Variational Approximation for a Poisson Mixed Model publication-title: Statistica Sinica – start-page: 568 year: 2015 ident: e_1_3_2_76_1 article-title: Automatic Variational Inference in Stan publication-title: Neural Information Processing Systems – ident: e_1_3_2_80_1 doi: 10.1007/978-1-4899-2696-8 – year: 2015 ident: e_1_3_2_130_1 publication-title: Stan Modeling Language Users Guide and Reference Manual, Version 2.8.0. New York: Columbia University – start-page: 844 year: 2010 ident: e_1_3_2_139_1 article-title: Bayesian Gaussian Process Latent Variable Model publication-title: Artificial Intelligence and Statistics – ident: e_1_3_2_148_1 doi: 10.1214/11-BA631 – start-page: 2095 year: 2015 ident: e_1_3_2_114_1 article-title: Celeste: Variational Inference for a Generative Model of Astronomical Images publication-title: International Conference on Machine Learning – start-page: 1441 year: 2015 ident: e_1_3_2_50_1 article-title: Linear Response Methods for Accurate Covariance Estimates from Mean Field Variational Bayes publication-title: Neural Information Processing Systems – ident: e_1_3_2_39_1 doi: 10.1214/aos/1176344611 – ident: e_1_3_2_73_1 doi: 10.1016/j.neuroimage.2007.09.005 – ident: e_1_3_2_133_1 doi: 10.1109/TPAMI.2008.157 – ident: e_1_3_2_5_1 doi: 10.1162/089976698300017746 – ident: e_1_3_2_161_1 doi: 10.1016/j.neuroimage.2008.02.059 – ident: e_1_3_2_70_1 doi: 10.1093/bioinformatics/bth917 – start-page: 324 year: 2016 ident: e_1_3_2_113_1 article-title: Hierarchical Variational Models publication-title: International Conference on Machine Learning – ident: e_1_3_2_88_1 doi: 10.1186/1471-2105-11-58 – ident: e_1_3_2_142_1 doi: 10.1016/S0893-6080(02)00040-0 – volume: 14 start-page: 2239 year: 2013 ident: e_1_3_2_30_1 article-title: Gaussian Kullback-Leibler Approximate Inference publication-title: The Journal of Machine Learning Research – start-page: 1 year: 2001 ident: e_1_3_2_69_1 article-title: Learning Flexible Sprites in Video Layers publication-title: Computer Vision and Pattern Recognition – ident: e_1_3_2_13_1 doi: 10.1613/jair.567 – start-page: 2888 year: 2012 ident: e_1_3_2_57_1 article-title: Fast Variational Inference in the Conjugate Exponential Family publication-title: Neural Information Processing Systems – ident: e_1_3_2_163_1 doi: 10.1142/S0219720004000508 – ident: e_1_3_2_123_1
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Snippet	One of the core problems of modern statistics is to approximate difficult-to-compute probability densities. This problem is especially important in Bayesian...
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SubjectTerms	Algorithms Americans artificial intelligence Bayesian analysis Bayesian theory catalytic activity Closeness Computationally intensive methods Density Families & family life Inference Machine learning Markov analysis Markov chain Markov chains mixtures Optimization Probability probability distribution Review Sampling Scholarship Statistical analysis Statistical computing Statistical inference Statistics
Title	Variational Inference: A Review for Statisticians
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