Accelerated High-Accuracy Sampling from a Warm Start via the Proximal Bouncy Particle Sampler
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Abstract (arXiv)
We study the problem of sampling from μ(dx)propto e-V(x),dx on ℝd, where V is α-strongly convex and β-smooth, and write kappa:=β/α. We design and analyze the Proximal Bouncy Particle Sampler (Proximal BPS), a new sampler that combines ideas from the proximal sampler and the bouncy particle sampler. From a warm start initialization with O(1) R'enyi divergence w.r.t. μ, Proximal BPS returns a sample whose law is varepsilon-close to μ in total variation distance using widetilde O(√kappa,d1/4 ,polylog(1/varepsilon)) gradient queries in expectation.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 11 of its 27 references that are in the map. First posted on arXiv 7 Sep 2026.
Builds on
11 of 27 references.
References · 11
- 2020Structured Logconcave Sampling with a Restricted Gaussian Oraclecited by 86
- 2022Improved analysis for a proximal algorithm for samplingcited by 73
- 2020Optimal dimension dependence of the Metropolis-Adjusted Langevin Algorithmcited by 57
- 2023Faster high-accuracy log-concave sampling via algorithmic warm startscited by 45
- 2021Minimax Mixing Time of the Metropolis-Adjusted Langevin Algorithm for Log-Concave Samplingcited by 44
- 2023Improved dimension dependence of a proximal algorithm for samplingcited by 30
- 2015The Bouncy Particle Sampler: A Non-Reversible Rejection-Free Markov Chain Monte Carlo Methodcited by 27
- 2026High-accuracy sampling for diffusion models and log-concave distributionscited by 16
- 2020The Boomerang Samplercited by 10
- 2026Exact simulation of diffusions and improved algorithms for log-concave samplingcited by 3
- 2026Windowed thinning and query complexity for the bouncy particle and Zigzag samplerscited by 1
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Citing papers per year: 2026: 2.
2 papers.