For large datasets, the Zig-Zag sampler with control variates draws effectively independent posterior samples at O(1) cost per sample in stationarity, while vanilla sub-sampling and canonical Zig-Zag cost O(n).
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Large sample scaling analysis of the Zig-Zag algorithm for Bayesian inference
For large datasets, the Zig-Zag sampler with control variates draws effectively independent posterior samples at O(1) cost per sample in stationarity, while vanilla sub-sampling and canonical Zig-Zag cost O(n).