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Research map / Learning theory and algorithms / Matrix and tensor methods

Compact Matrix Factorization With Dependent Subspaces

CVPR 2017 · Learning theory and algorithms › Matrix and tensor methods · approach: Matrix completion and factorization · 8 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Combine local subspace constraints with a global rank constraintmatrix completion · Paper sequence, missing pointsreconstruction error: 3.27e3 -> 2.86e2Helped
Combine local subspace constraints with a global rank constraintmatrix completion · Back sequence, missing pointsreconstruction error: 1.9e3 -> 1.4e3Helped
Combine local subspace constraints with a global rank constraintmatrix completion · Heart sequence, missing pointsreconstruction error: 4.4e3 -> 3.6e3Helped
Use the unified model instead of independent local subspacesmatrix completion · Paper sequence, missing pointsreconstruction error: 2.79e4 -> 2.86e2Helped
Use the unified model instead of independent local subspacesmatrix completion · Back sequence, missing pointsreconstruction error: 1.1e5 -> 1.4e3Helped
Use the unified model instead of independent local subspacesmatrix completion · Heart sequence, missing pointsreconstruction error: 2.2e5 -> 3.6e3Helped
Use the unified model instead of the global modelmatrix completion · Paper sequence, visible pointsreconstruction error: 3.95e1 -> 1.07e2Hurt
Use the unified model instead of the global modelmatrix completion · Back sequence, visible pointsreconstruction error: 5.3e2 -> 6.9e2Hurt
Use the unified model instead of the global modelmatrix completion · Heart sequence, visible pointsreconstruction error: 1.1e3 -> 1.5e3Hurt
Use the proposed factorization rather than the strongest reported baselineHopkins155 matrix completion · tracking failuresuccessful instances: 88 (56.8%) -> 148 (95.5%)Helped
Use the proposed factorization rather than competing methodsHopkins155 matrix completion · uniform missing entriessuccessful instancesNo clear effect

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