Yes, but did it work?: Evaluating variational inference
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A4 Artikkeli konferenssijulkaisussa
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Date
2018-01-01
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en
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9
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35th International Conference on Machine Learning, ICML 2018, Volume 12, pp. 8887-8895, Proceedings of Machine Learning Research ; 80
Abstract
While it's always possible to compute a variational approximation to a posterior distribution, it can be difficult to discover problems with this approximation". We propose two diagnostic algorithms to alleviate this problem. The Paretosmoothed importance sampling (PSIS) diagnostic gives a goodness of fit measurement for joint distributions, while simultaneously improving the error in the estimate. The variational simulationbased calibration (VSBC) assesses the average performance of point estimates.Description
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Yao, Y, Vehtari, A, Simpson, D & Gelman, A 2018, Yes, but did it work? Evaluating variational inference . in J Dy & A Krause (eds), 35th International Conference on Machine Learning, ICML 2018 . vol. 12, Proceedings of Machine Learning Research, no. 80, International Machine Learning Society, pp. 8887-8895, International Conference on Machine Learning, Stockholm, Sweden, 10/07/2018 . < http://proceedings.mlr.press/v80/yao18a.html >