The dually flat structure introduced by Amari-Nagaoka is highlighted in information geometry and related fields. In practical applications, however, the underlying pseudo-Riemannian metric may often be degenerate, and such an excellent geometric structure is rarely defined on the entire space. To fix this trouble, in the present paper, we propose a novel generalization of the dually flat structure for a certain class of singular models from the viewpoint of Lagrange and Legendre singularity theory - we introduce a quasi-Hessian manifold endowed with a possibly degenerate metric and a particular symmetric cubic tensor, which exceeds the concept of statistical manifolds and is adapted to the theory of (weak) contrast functions. In particular, we establish Amari-Nagaoka's extended Pythagorean theorem and projection theorem in this general setup, and consequently, most of applications of these theorems are suitably justified even for such singular cases. This work is motivated by various interests with different backgrounds from Frobenius structure in mathematical physics to Deep Learning in data science.
翻译:由Amari-Nagaoka引入的双板结构在信息几何学和相关领域中得到了突出的强调。然而,在实际应用中,基础伪里曼尼测量仪往往会退化,而且在整个空间中很少界定出这样一个极好的几何结构。为了解决这个问题,我们在本文件中提议从Lagrange和Luntre独一理论的角度,对某类单一模型的双板结构进行新颖的概括化,我们引入了一种准赫斯式的元件,配有一种可能退化的度量和特定对称立立立方的立方体,它超越了统计方体的概念,并适应了(弱)对比功能的理论。特别是,我们建立了Amari-Nagaokaka的扩展Pythagorean 理论,并在此总体设置中投射了理论,因此,这些理论的大部分应用甚至对于这类奇特案例都是有道理的。这项工作的动机来自从数学物理学的Frobenius结构到数据科学的深层学习的不同背景的不同利益。