An “information-theoretically optimal” quantization scheme with respect to a distribution pop over x ∈ R (in our case, x represents a model weight) using B bits is one that partitions R so that each of K = 2B …

Uniform scalar quantization is the simplest and often most practical approach to quantization. Before reaching this conclusion, two approaches to optimal scalar quantizers were taken.

topics in quantization which are mostly used for sub-INT8 quantization. We will first discuss simulated quantiza-tion and its difference with integer-only quantization in Section IV-A. Afterward, we will …

post-training quantization (PTQ): a pre-trained model is calibrated using finetuning data (e.g., a small subset of training data) to compute the clipping ranges and the scaling factors.

Quantization ideas with weighted quadratic distortion measures have applications outside of traditional data compression, especially to statistical classification, clustering, and machine learning.

Quantization values are the “centroid” of their region. Boundaries of the quantization regions are the midpoint of the quantization values. Clearly 1 depends on 2 and visa-versa. The two can be solved …

nProblem : For a signal uwith given pdf find a quantizer with Nrepresentative levels such that. pu(u) variance of quantization error min → . nSolution : Lloyd-Max quantizer (Lloyd, 1957; Max, 1960)