Duality induced by an embedding structure of determinantal point process

Autor:	Hino, Hideitsu, Yano, Keisuke
Rok vydání:	2024
Předmět:	Mathematics - Statistics Theory Computer Science - Information Theory Statistics - Machine Learning
Druh dokumentu:	Working Paper
Popis:	This paper investigates the information geometrical structure of a determinantal point process (DPP). It demonstrates that a DPP is embedded in the exponential family of log-linear models. The extent of deviation from an exponential family is analyzed using the $\mathrm{e}$-embedding curvature tensor, which identifies partially flat parameters of a DPP. On the basis of this embedding structure, the duality related to a marginal kernel and an $L$-ensemble kernel is discovered.
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2404.11024 Zobrazit plný text záznamu View this record from Arxiv