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Modern applications of Bayesian inference involve models that are sufficiently complex that the corresponding posterior distributions are intractable and must be approximated.
On information and sufficiency
Kullback, S. and Leibler, R. A. (1951) · 1951
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Some inequalities satisfied by the quantities of information of Fisher and Shannon
Stam, A. J. (1959) · 1959
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Construction of nearest points in the l p l_{p} , p p even, and l ∞ l_{\infty} norms
Karlovitz, L. (1970) · 1970
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Doubly stochastic variational Bayes for non-conjugate inference
Titsias, M. and Lázaro-Gredilla, M. (2014) · 1979
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Entropy and the central limit theorem
Barron, A. R. (1986) · 1986
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The simplex and projective scaling algorithms as iteratively reweighted least squares methods
Stone, R. E. and Tovey, C. A. (1991) · 1991
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Iterative reweighted least-squares design of FIR filters
Burrus, C. S., Barreto, J., and Selesnick, I. W. (1994) · 1994
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A variational approach to Bayesian logistic regression models and their extensions
Jaakkola, T. and Jordan, M. (1997) · 1997
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Information Theory and Statistics
Kullback, S. (1997) · 1997
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On the momentum term in gradient descent learning algorithms
Qian, N. (1999) · 1999
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Fisher information inequalities and the central limit theorem
Johnson, O. and Barron, A. (2004) · 2004
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Information Theory and the Central Limit Theorem
Johnson, O. T. (2004) · 2004
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Convex statistical distances
Liese, F. and Vajda, I. (2007) · 2007
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Asymptotic Theory of Statistics and Probability
DasGupta, A. (2008) · 2008
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Variational inference for large-scale models of discrete choice
Braun, M. and McAuliffe, J. (2010) · 2010
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Black box variational inference
Ranganath, R., Gerrish, S., and Blei, D. (2014) · 2014
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Rényi divergence and Kullback-Leibler divergence
Van Erven, T. and Harremos, P. (2014) · 2014
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Rényi divergence variational inference
Li, Y. and Turner, R. E. (2016) · 2016
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Stein variational gradient descent: A general purpose Bayesian inference algorithm
Liu, Q. and Wang, D. (2016) · 2016
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Bayesian information in an experiment and the Fisher information distance
Walker, S. G. (2016) · 2016
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Variational inference: A review for statisticians
Blei, D. M., Kucukelbir, A., and McAuliffe, J. D. (2017) · 2017
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Park, S., Serpedin, E., and Qaraqe, K. (2012) · 2012
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Auto-encoding variational Bayes
Kingma, D. P. and Welling, M. (2013) · 2013
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Variational inference in nonconjugate models
Wang, C. and Blei, D. M. (2013) · 2013
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Assigning a value to a power likelihood in a general Bayesian model
Holmes, C. and Walker, S. (2017) · 2017
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Practical bounds on the error of Bayesian posterior approximations: A nonasymptotic approach
Huggins, J. H., Campbell, T., Kasprzak, M., and Broderick, T. (2018) · 2018
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