一篇新的研究笔记提出将偏最小二乘法（PLS）视为一种线性化自注意力。这种观点表明PLS可以在神经网络的框架内进行分析。此外，PLS固有的降维和预测变量选择可能意味着自注意力机制包含一定程度的归一化以增强学习。 AI
影响 通过与已建立的统计方法建立联系，提出了一个理解和潜在改进自注意力机制的新理论视角。
排序理由 该集群包含一篇讨论两种机器学习概念之间新理论联系的学术论文。
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arXiv:2605.28592v1 Announce Type: new Abstract: This note provides an interesting observation on casting partial least square (PLS) as a linearized self-attention so that PLS may be studied within the neural network paradigm. On the other hand, the dimensionality reduction and se…
This note provides an interesting observation on casting partial least square (PLS) as a linearized self-attention so that PLS may be studied within the neural network paradigm. On the other hand, the dimensionality reduction and selection of predictors in PLS may indicate that s…
This note provides an interesting observation on casting partial least square (PLS) as a linearized self-attention so that PLS may be studied within the neural network paradigm. On the other hand, the dimensionality reduction and selection of predictors in PLS may indicate that s…