I understand there are K prototypes (centroid) in each subspace. And there are C disjoint subspaces. But how are subspaces chosen? Do we naively split the vector space?
For softmax example, if the original 512-element vector is x = (x0, x1, ..., x511), and we want to compress the vector to 4-bytes (and K=16 using 4 bits per prototype). There should be 8 subspaces. Does that mean we break the 512-element vector into eight 64-element sub-vectors? Like (x0,...,x63), (x64,...,x127),(x128,...,x191), ..., (x448,...,x511) and each sub-vector e.g. (x0,...,x64) is compressed into 4 bit? It looks like a lot of information are compressed into to zeros and lost.
I wonder in the image filtering field (such as Sobel and Gaussian filter), how to choose a compression ratio in order to get a reasonable good image quality.
For softmax example, if the original 512-element vector is x = (x0, x1, ..., x511), and we want to compress the vector to 4-bytes (and K=16 using 4 bits per prototype). There should be 8 subspaces. Does that mean we break the 512-element vector into eight 64-element sub-vectors? Like (x0,...,x63), (x64,...,x127),(x128,...,x191), ..., (x448,...,x511) and each sub-vector e.g. (x0,...,x64) is compressed into 4 bit? It looks like a lot of information are compressed into to zeros and lost.
I wonder in the image filtering field (such as Sobel and Gaussian filter), how to choose a compression ratio in order to get a reasonable good image quality.