论文标题
具有条件或隐藏数据的指数家庭的始终匹配条件
Moment-Matching Conditions for Exponential Families with Conditioning or Hidden Data
论文作者
论文摘要
用指数家庭的最大似然学习会导致足够的统计数据的力矩匹配，这是一个经典的结果。这可以推广到有条件的指数族和/或当隐藏数据时。该文档对这些广义的力矩匹配条件以及独立的推导提供了第一原理的解释。
Maximum likelihood learning with exponential families leads to moment-matching of the sufficient statistics, a classic result. This can be generalized to conditional exponential families and/or when there are hidden data. This document gives a first-principles explanation of these generalized moment-matching conditions, along with a self-contained derivation.
