异质输入融合下的良性过拟合研究

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   arXiv · Statistics Machine Learning

   异构输入融合下的良性过拟合研究

   该研究在异构高斯设计下考察最小范数线性插值，比较两个统计相关输入块及其融合，并固定底层总体任务。回归方面，作者给出全谱协方差证书，证明其渐近性质与截断阈值无关，并被任何与两个边缘分布一致的正半定联合协方差保持；但在认证机制之外，两个良性边缘仍可能产生有害融合。

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