Vector Quantization (k-means problem)

Given a data set $X$ of d-dimensional numeric vectors and a number $k$ find a codebook $C$ of $k$ d-dimensional vectors such that the sum of square distances of each $x \in X$ to the respective nearest $c \in C$ is as small as possible. This is also known as the k-means problem and is known to be NP-hard.