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New Proximal Bouncy Particle Sampler accelerates high-accuracy sampling

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Researchers have developed the Proximal Bouncy Particle Sampler (Proximal BPS), a novel algorithm designed for efficient sampling from probability distributions. This new sampler combines techniques from proximal and bouncy particle samplers to achieve high accuracy with fewer gradient queries. The Proximal BPS is particularly effective for distributions where the potential function is strongly convex and smooth, offering a theoretical guarantee on its performance. AI

RANK_REASON The cluster contains an academic paper detailing a new sampling algorithm. [lever_c_demoted from research: ic=1 ai=0.7]

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New Proximal Bouncy Particle Sampler accelerates high-accuracy sampling

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The cluster contains an academic paper detailing a new sampling algorithm. [lever_c_demoted from research: ic=1 ai=0.7]
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COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · Fan Chen, Sinho Chewi, Jianfeng Lu, Matthew S Zhang ·

    Accelerated High-Accuracy Sampling from a Warm Start via the Proximal Bouncy Particle Sampler

    arXiv:2609.06905v1 Announce Type: cross Abstract: We study the problem of sampling from $\mu(\mathrm{d}x)\propto e^{-V(x)}\,\mathrm{d}x$ on $\mathbb{R}^d$, where $V$ is $\alpha$-strongly convex and $\beta$-smooth, and write $\kappa:=\beta/\alpha$. We design and analyze the Proxim…

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