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Practical and Matching Gradient Variance Bounds for Black-Box
  Variational Bayesian Inference

Practical and Matching Gradient Variance Bounds for Black-Box Variational Bayesian Inference

18 March 2023
Kyurae Kim
Kaiwen Wu
Jisu Oh
J. Gardner
    BDL
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Papers citing "Practical and Matching Gradient Variance Bounds for Black-Box Variational Bayesian Inference"

4 / 4 papers shown
Title
Stochastic variance-reduced Gaussian variational inference on the Bures-Wasserstein manifold
Stochastic variance-reduced Gaussian variational inference on the Bures-Wasserstein manifold
Hoang Phuc Hau Luu
Hanlin Yu
Bernardo Williams
Marcelo Hartmann
Arto Klami
DRL
38
0
0
03 Oct 2024
Provably Scalable Black-Box Variational Inference with Structured
  Variational Families
Provably Scalable Black-Box Variational Inference with Structured Variational Families
Joohwan Ko
Kyurae Kim
W. Kim
Jacob R. Gardner
BDL
30
2
0
19 Jan 2024
A Rule for Gradient Estimator Selection, with an Application to
  Variational Inference
A Rule for Gradient Estimator Selection, with an Application to Variational Inference
Tomas Geffner
Justin Domke
37
6
0
05 Nov 2019
Linear Convergence of Gradient and Proximal-Gradient Methods Under the
  Polyak-Łojasiewicz Condition
Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition
Hamed Karimi
J. Nutini
Mark W. Schmidt
139
1,199
0
16 Aug 2016
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