Adaptive Canonical Correlation Analysis Based On Matrix Manifolds
  In this paper, we formulate the Canonical Correlation Analysis (CCA) problem on matrix manifolds. This framework provides a natural way for dealing with matrix constraints and tools for building efficient algorithms even in an adaptive setting. Finally, an adaptive CCA algorithm is proposed and applied to a change detection problem in EEG signals. 
Florian Yger (LITIS), Maxime Berar (LITIS), Gilles Gasso (INSA de   Rouen), Alain Rakotomamonjy (INSA de Rouen)
cs.LG stat.ML