A Manifold Approach to Learning Mutually Orthogonal Subspaces

Francisco Garcia
Francisco Garcia

CoRR, Volume abs/1703.02992, 2017.

Cited by: 0|Views18


Although many machine learning algorithms involve learning subspaces with particular characteristics, optimizing a parameter matrix that is constrained to represent a subspace can be challenging. One solution is to use Riemannian optimization methods that enforce such constraints implicitly, leveraging the fact that the feasible paramet...More



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