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paper.md

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This suggests that each observation $x_i \in \mathrm{rows}(X)$ can be well-approximated by a linear combination of $k$ basis vectors (the rows of $V$):
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[$$x_i \approx \theta_i = a_i V$$]{label="eq:pca"}
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$$x_i \approx \theta_i = a_i V \label{pca}$$
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for $i = 1, \dots, n$.
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