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Local and Global Contraction Principles for MCMC Mixing

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arXiv:2606. 03033v1 Announce Type: cross Abstract: We develop a contraction-based framework for proving mixing-time bounds for Markov chain Monte Carlo algorithms.

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Authors: Alireza Daeijavad, Shahab Asoodeh
Released: 2026-06-03 (2mo ago)
Topic: Related to current project
Relation to my work: Read next because Local and Global Contraction Principles for MCMC Mixing overlaps with clean result "Language-mismatch LoRA SFT on Qwen2.5-7B leaks the trained completion language into bystander directives the model was never trained on, absent under same-language SFT (LOW confidence)", clean result "Training one persona to emit a [ZLT] marker without bystanders adopting it has a one-cell-wide LR x epochs window on Qwen2.5-7B-Instruct (LOW confidence)", clean result "A pretraining-data-poisoned Qwen3-4B backdoor only fires on the exact trigger tokens — paraphrases don't activate it, and base-model similarity to the trigger doesn't predict which inputs fire (MODERATE confidence)". Matching terms: rect, under, rate, project, control, chain. Source: arxiv stat.ML (Machine Learning).
arXiv: 2606.03033

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