5 ms·
r is a single value per vector. You don't have to quantize it, you can keep it and quantize the billion+ other coordinates of the vector.
by amitport 6mo ago
r is a single value per vector. You don't have to quantize it, you can keep it and quantize the billion+ other coordinates of the vector.
- mungoman2 6mo agoWhat they're saying is that the error for a vector increases with r, which is true. Trivially, with r=0, the error is 0, regardless of how heavily the direction is quantized. Larger r means larger absolute error in the reconstructed vector.
- amitport 6mo agoYes, the important part is that the normalized error does not increase with the dimension of the vector (which does happen when using biased quantizers) It is expected that bigger vectors have proportionally bigger error, nothing can be done by the quantizer about that.
- moktonar 6mo agoExcept maybe storing another smaller vector for the difference with the original data an also quantize that maybe recursively