Dimensionality reduction: Some Assumptions
	• High-dimensional data often lies on or near a much lower dimensional, curved manifold. • A good way to represent data points is by their low-dimensional coordinates. • The low-dimensional representation of the data should capture information about high- dimensional pairwise distances.