I read the below notation from a machine learning paper. $G_d$ is called a grid in $[0,1]^{d \times n}$ by the author. My understanding is: the vector entries are now restricted on the grid points instead of arbitrary values within the continous interval $[0, 1]$. In other words, $G_d$ can also be called a discretized vector space.
$$G_d=\{ 0,\delta, ..., 1-\delta \}^{d \times n} \text{in which } 0<\delta<1~~~~d,n \in \mathbf{N}^+$$
Please correct me if my interpretation is wrong.
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Yiwei Jiang
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