Beyond Self-Repellent Kernels: History-Driven Target Towards Efficient Nonlinear MCMC on General Graphs

Jie Hu; Yi-Ting Ma; Do Young Eun

2025 ICML ICML 2025

Beyond Self-Repellent Kernels: History-Driven Target Towards Efficient Nonlinear MCMC on General Graphs

Abstract

No abstract available. No abstract was captured for this paper when its proceedings were scraped - most often an older edition published without one online. How the corpus is built.

🌉 Interdisciplinary Bridge - Artificial Intelligence and Mathematics & Optimization

Authors

Jie Hu, Yi-Ting Ma, Do Young Eun

Topics

Machine Learning > Optimization & Theory > Optimization Mathematics & Optimization > Mathematics > Graph Theory

Keywords

markov chain monte carlo transition kernel self-repellent random walk graph sampler history-driven target least recently used cache

Download PDF