2026
COLT
COLT 2026
The Geometry of Efficient Nonconvex Sampling
Abstract
We present an efficient algorithm for uniformly sampling from an arbitrary compact body $\mathcal{X} \subset \mathbb{R}^n$ from a warm start under isoperimetry and a natural volume growth condition. Our result provides a substantial common generalization of known results for convex bodies and star-shaped bodies. The complexity of the algorithm is polynomial in the dimension, the Poincar{é} constant of the uniform distribution on $\mathcal{X}$ and the volume growth constant of the set $\mathcal{X}$.
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Interdisciplinary Bridge
- Artificial Intelligence and Mathematics & Optimization