no code implementations • 6 Nov 2023 • Andreas Galanis, Alkis Kalavasis, Anthimos Vardis Kandiros
For general $H$-colorings, we show that standard conditions that guarantee sampling, such as Dobrushin's condition, are insufficient for one-sample learning; on the positive side, we provide a general condition that is sufficient to guarantee linear-time learning and obtain applications for proper colorings and permissive models.
no code implementations • 6 Apr 2017 • Sejun Park, Yunhun Jang, Andreas Galanis, Jinwoo Shin, Daniel Stefankovic, Eric Vigoda
The Gibbs sampler is a particularly popular Markov chain used for learning and inference problems in Graphical Models (GMs).
