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作者您好,我阅读文章的 Anchor Re-weighting 章节后,理解的思路是:1. 将 $P(Y=i | X)$ 和 $P(Y=C | X)$ 相比后,发现任意两个标签的概率分布之间都呈线性关系 2. 既然他们彼此间呈线性关系,那么就可以引入一个可学习的参数 $\beta$ 对现有的 $A(q, p_i)$ 进行线性调整。请问我这样理解的对吗?如果理解不准确的话,可以更详细的解释一下 式(7) 到 式(9) 的过程吗,谢谢!
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对,是这个意思,就是在(7)里尝试引入(8)里的\beta_0,然后考虑到P(Y=i|X)和A(q,p_i)近似成正比(式子6里提了)所以得到(9)
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作者您好,我阅读文章的 Anchor Re-weighting 章节后,理解的思路是:1. 将$P(Y=i | X)$ 和 $P(Y=C | X)$ 相比后,发现任意两个标签的概率分布之间都呈线性关系 2. 既然他们彼此间呈线性关系,那么就可以引入一个可学习的参数 $\beta$ 对现有的 $A(q, p_i)$ 进行线性调整。请问我这样理解的对吗?如果理解不准确的话,可以更详细的解释一下 式(7) 到 式(9) 的过程吗,谢谢!
The text was updated successfully, but these errors were encountered: