A Geometric Perspective on Dimensionality Reduction

Question How can we detect low dimensional structure in high dimensional data? Applications  Digital image and speech processing  Analysis of neuronal populations  Gene expression microarray data  Visualization of large networks Does the data mostly lie in a subspace? If so, what is its dimensionality? If the data are nonlinear distributed, how can we handle this?