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Poisson-Minibatching for Gibbs Sampling with Convergence Rate Guarantees

Poisson-Minibatching for Gibbs Sampling with Convergence Rate Guarantees

Ruqi Zhang
Christopher De Sa
ArXiv (abs)PDFHTML

Papers citing "Poisson-Minibatching for Gibbs Sampling with Convergence Rate Guarantees"

5 / 5 papers shown
Title
DP-Fast MH: Private, Fast, and Accurate Metropolis-Hastings for Large-Scale Bayesian Inference
DP-Fast MH: Private, Fast, and Accurate Metropolis-Hastings for Large-Scale Bayesian Inference
Wanrong Zhang
Ruqi Zhang
65
4
0
10 Mar 2023
Fast Doubly-Adaptive MCMC to Estimate the Gibbs Partition Function with Weak Mixing Time Bounds
Fast Doubly-Adaptive MCMC to Estimate the Gibbs Partition Function with Weak Mixing Time Bounds
Shahrzad Haddadan
Zhuang Yue
Cyrus Cousins
E. Upfal
33
7
0
14 Nov 2021
Where Is the Normative Proof? Assumptions and Contradictions in ML Fairness Research
Where Is the Normative Proof? Assumptions and Contradictions in ML Fairness Research
A. Feder Cooper
70
7
0
20 Oct 2020
AMAGOLD: Amortized Metropolis Adjustment for Efficient Stochastic Gradient MCMC
AMAGOLD: Amortized Metropolis Adjustment for Efficient Stochastic Gradient MCMC
Ruqi Zhang
A. Feder Cooper
Christopher De Sa
81
18
0
29 Feb 2020
Improving Sampling Accuracy of Stochastic Gradient MCMC Methods via Non-uniform Subsampling of Gradients
Improving Sampling Accuracy of Stochastic Gradient MCMC Methods via Non-uniform Subsampling of Gradients
Ruilin Li
Xin Wang
H. Zha
Molei Tao
34
4
0
20 Feb 2020