classical scaling is perhaps the main method for multidimensional scaling (mds), which is an area of statistics (although initiated in psychometrics) where the central task is the embedding of a weighted graph as a configuration of points in a euclidean space in such a way as to match, as much as possible, the edges weights with the euclidean distance between the corresponding points. the presentation will introduce this old method (dating back to the 1930s) and then go over more recent advances (last 20 years) in terms of computation, perturbation bounds, and more.