Robust and Flexible Principal Directions via Flag Manifolds

The authors present a unifying framework for computing robust principal directions of Euclidean and non-Euclidean data using flag manifolds. This framework enables the development of novel dimensionality reduction algorithms by modifying the flag type or altering the norms used in the optimization.