The parameters

The network parameters, to be optimized/learned:

1. $\boldsymbol{a}$ represents the visible bias, a vector of same length $M$ as $\boldsymbol{x}$.
2. $\boldsymbol{b}$ represents the hidden bias, a vector of same length $N$ as $\boldsymbol{h}$.
3. $\boldsymbol{W}$ represents the interaction weights, a matrix of size $M\times N$.

Note that we have specified the lengths of $bm{x}$ and $\boldsymbol{h}$. These lengths define the number of visible and hidden units, respectively.

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