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math.PR2026
Local Geometric Mixing via Dobrushin Contraction with Applications to Diffusion Path Monte Carlo and the Proximal Sampler
Stefan Oberdörster
Local geometric mixing localizes geometric mixing by requiring geometric convergence to equilibrium in total variation only over finitely many transitions. It accommodates local co…
math.PR2024
Ballistic Convergence in Hit-and-Run Monte Carlo and a Coordinate-free Randomized Kaczmarz Algorithm
Nawaf Bou-Rabee, Andreas Eberle, Stefan Oberdörster
Hit-and-Run is a coordinate-free Gibbs sampler, yet the quantitative advantages of its coordinate-free property remain largely unexplored beyond empirical studies. In this paper, w…
math.PR2024
Mixing of the No-U-Turn Sampler and the Geometry of Gaussian Concentration
Nawaf Bou-Rabee, Stefan Oberdörster
We prove that the mixing time of the No-U-Turn Sampler (NUTS), when initialized in the concentration region of the canonical Gaussian measure, scales as , up to logarithmi…