irtrdsvd

 IRTRDSVD   Compute dominant SVD of a rectangular matrix

 This computes the dominant singular values and singular vectors of a 
 rectangular matrix A by optimizing the function 
   f(U,V) = trace(U'*A*V*N)
 on the manifold St(k,m) x St(k,n) using the Riemannian Trust-Region 
 with truncated CG inner solver.

 The manifold St(k,m) x St(k,n) is the product of two orthogonal Stiefel manifolds:
   St(k,n) = {X \in R^{n x k} such that X^T X = I_k}

 S = irtrdsvd(A,k) returns the dominant k singular values
 [U,S,V] = irtrdsvd(A,k) returns the dominant k singular vectors and values
 [U,S,V,stats] = irtrdsvd(A,k) returns in addition some statistics from the solver.
 See IRTR for info.

 irtrdsvd(A,k,params) allows the user to specify parameters that are passed 
 to the IRTR solver.
   params.x0        - initial iterate: x.U orthonormal and x.V orthonormal
   params.Delta_bar - maximum trust-region radius
   params.Delta0    - initial trust-region radius
   params.epsilon   - Outer Convergence tolerance (absolute)

 See also irtr, rtreig, rtreig2, rtrflat