Optimizing Partitions to Speed Up Markov Chains
michaelchchoi · x · 2026-07-18
A new paper discusses how to select the optimal bipartition for finite Markov chains to accelerate mixing under group-averaging transformations.
The author explores the optimization problem for "two-block averaging kernels": how to split the state space into two blocks, or generalize to k blocks, for faster chain convergence. The post also notes an approximation idea akin to spectral clustering, but employing the bottom-k eigenvalues instead of the standard top eigenvalues perspective.
Related event: Optimizing Markov Chains via Spectral Information(2 posts)→
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