分布式表示的几何代数模型
Geometric Algebra Model of Distributed Representations
摘要：
基于遗传算法的形式化表示方法是目前发展起来的分布式表示模型的一种替代方法，这些分布式表示模型包括Smolensky的张量积、全息简化表示（HRR）和二进制飞溅码（BSC）。卷积被几何积所取代，几何积可以用几何来解释，这似乎是更高概念可视化的最自然语言。本文回顾了GA模型背后的主要思想，并研究了识别测试结果，使用内积和裁剪版本的矩阵表示。研究了偶然叶片相等对识别的影响。最后，GA模型的效率相比，以前开发的模型。
英文摘要：
Formalism based on GA is an alternative to distributed representation models developed so far --- Smolensky's tensor product, Holographic Reduced Representations (HRR) and Binary Spatter Code (BSC). Convolutions are replaced by geometric products, interpretable in terms of geometry which seems to be the most natural language for visualization of higher concepts. This paper recalls the main ideas behind the GA model and investigates recognition test results using both inner product and a clipped version of matrix representation. The influence of accidental blade equality on recognition is also studied. Finally, the efficiency of the GA model is compared to that of previously developed models.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
