研究人员为对数凹分布采样开发了一种新的、统一的复杂性界限。该界限接近最优，并适用于各种情况，包括约束和适定密度。该分析为提升分布的庞加莱常数提供了改进的界限，从而提高了收敛速度。 AI
排序理由 该集群包含一篇学术论文，详细介绍了对数凹分布采样的新理论界限。
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arXiv:2606.12694v1 Announce Type: cross Abstract: We give a simple, unified, and nearly tight bound for sampling arbitrary logconcave distributions from a warm start using the In-and-Out algorithm along with exponential lifting. The main new ingredient in the analysis is an impro…
We give a simple, unified, and nearly tight bound for sampling arbitrary logconcave distributions from a warm start using the In-and-Out algorithm along with exponential lifting. The main new ingredient in the analysis is an improved bound on the Poincaré constant of a lifted dis…