维度的维度维度的维度
Brett D Roads1, Bradley C Love1
1Department of Experimental Psychology, University College London, London, WC1E, UK.
Trends in cognitive sciences
|August 17, 2024
概括
认知科学家使用潜在的表示空间或嵌入来分析数据. 本综述阐明了不同的维度概念如何影响这些嵌入在认知科学研究中的解释和使用.
科学领域:
- 认知科学 认知科学
- 神经科学是一个神经科学.
- 机器学习 机器学习
背景情况:
- 认知科学家从不同的数据类型中推断出多维表示 (嵌入).
- 嵌入的特性,如可解释性和维度性,随着推理方法的不同而有所不同.
- 现有的嵌入式和图形表示之间的比较可能会误导.
研究的目的:
- 审查和澄清认知科学中的"维度"概念.
- 为了指导隐藏的表示空间的解释和应用.
- 解决嵌入的可比性和可解释性挑战.
主要方法:
- 在认知科学中对表示空间的文献综述.
- 在各种数据类型中分析"维度"的不同概念.
- 嵌入属性和推理程序的概念合成.
主要成果:
- 推理程序显著影响嵌入属性.
- 维度的全球解释性并不总是可以保证的.
- 维度并不总是可以在不同的嵌入式中直接比较.
- 多维空间和图形表示之间的区别往往是人为的.
结论:
- 了解"维度"概念对于正确解释嵌入非常重要.
- 研究人员应该注意推断方法对表示性质的影响.
- 需要对表现形式的细微视角,超越简单的多维空间.
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