BriefGPT.xyz
Mar, 2012
贝叶斯指数族投影用于耦合数据源
Bayesian exponential family projections for coupled data sources
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Arto Klami, Seppo Virtanen, Samuel Kaski
TL;DR
该文章介绍了将指数族扩展应用于多视角学习方法中，它基于EPCA的矩阵分解，以指数族的自然参数表示，同时提出了一种新的可用于所有因子分解的先验分布族，并演示了当高斯分布假设不成立时它的优越性。
Abstract
exponential family extensions
of
principal component analysis
(EPCA) have received a considerable amount of attention in recent years, demonstrating the growing need for basic modeling tools that do not assume th
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