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Ali Ghodsi Department of Statistics and Actuarial Science David R. Cheriton School of Computer Science University of Waterloo Joint work with Stephen Vavasis and Michael Biggs University of Waterloo. Nonnegative Matrix Factorization via Rank-one Downdate.
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Ali Ghodsi Department of Statistics and Actuarial Science David R. Cheriton School of Computer Science University of Waterloo Joint work with Stephen Vavasis and Michael Biggs University of Waterloo Nonnegative Matrix Factorization via Rank-one Downdate
-2.19 -3.19 -0.02 1.02 2 by 1965 560 by 1965 560 by 2 20 by 28 2 by 1 2 by 1 20 by 28
Power method • Computes the leading singular vectors/value (or eigenvector/value) of a matrix 1 2 while not converged 3 4 5 6 end
Naive approach to NMF using this observation 1 2 3 4 5 for all set 6 end for Without step 5, this will simply compute the SVD (Jordan's algorithm, Camille Jordan 1874. )
Modified power iteration: Demo Rank-1 submatrix A = Rank-1 submatrix
Modified power iteration: Demo v: 0.14 0.07 0.64 0.41 0.55 Rank-1 submatrix Rank-1 submatrix
Modified power iteration: Demo v: 0.0 0.00.64 0.41 0.55 Rank-1 submatrix Rank-1 submatrix
Modified power iteration: Demo v: 0.0 0.00.64 0.41 0.55 Rank-1 submatrix Rank-1 submatrix
u: Modified power iteration: Demo v: 0.0 0.00.64 0.410.55 0.16 0.21 0.22 0.44 0.74 0.20 Rank-1 submatrix Rank-1 submatrix
u: Modified power iteration: Demo v: 0.0 0.0 0.64 0.41 0.55 0.0 0.0 0.0 0.44 0.74 0.20 Rank-1 submatrix Rank-1 submatrix
u: Modified power iteration: Demo v: 0.0 0.0 0.64 0.41 0.55 0.0 0.0 0.0 0.44 0.74 0.20 Rank-1 submatrix Rank-1 submatrix
u: Modified power iteration: Demo v: 0.0 0.0 0.60 0.28 0.59 0.0 0.0 0.0 0.44 0.74 0.20 Rank-1 submatrix Rank-1 submatrix
u: Modified power iteration: Demo v: 0.0 0.0 0.60 0.28 0.59 0.0 0.0 0.0 0.44 0.74 0.20 Rank-1 submatrix Rank-1 submatrix
u: Modified power iteration: Demo v: 0.0 0.0 0.60 0.28 0.59 0.0 0.0 0.0 0.44 0.74 0.20 Rank-1 submatrix Rank-1 submatrix Zero-out!
Modified power iteration: Demo Rank-1 submatrix Anew =