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Robust Joint and Individual Variance Explained

CVPR 2017 · Vision-language and multimodal › Human and embodied modeling · approach: Scientific domain vision datasets · 20 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use robust ℓ1-RJIVE instead of JIVEjoint and individual component recovery · Synthetic data, all three configurationsjoint RRE: 0.5424 -> 5.5628e − 08; 0.83977 -> 8.9035e − 08; 1.3961 -> 2.427e − 07Helped
Use robust ℓ1-RJIVE instead of JIVEjoint and individual component recovery · Synthetic data, all three configurationsindividual RRE: 0.93488 -> 3.5073e − 08; 1.481 -> 5.8665e − 08; 2.1977 -> 2.3743e − 06Helped
Use robust ℓ1-RJIVE instead of COBEjoint and individual component recovery · Synthetic data, all three configurationsjoint RRE: 3.6403 -> 5.5628e − 08; 5.2902 -> 8.9035e − 08; 7.3973 -> 2.427e − 07Helped
Use robust ℓ1-RJIVE instead of COBEjoint and individual component recovery · Synthetic data, all three configurationsindividual RRE: 1.0956 -> 3.5073e − 08; 1.0945 -> 5.8665e − 08; 1.1808 -> 2.3743e − 06Helped
Add nuclear-norm regularization to ℓ1-RJIVEjoint and individual component recovery · Synthetic data, configuration (500, 500, 500, 5, 10, 10)joint RRE: 5.5628e − 08 -> 1.3338e − 08Helped
Add nuclear-norm regularization to ℓ1-RJIVEjoint and individual component recovery · Synthetic data, configuration (500, 500, 500, 5, 10, 10)individual RRE: 3.5073e − 08 -> 1.1897e − 08Helped
Add nuclear-norm regularization to ℓ1-RJIVEjoint and individual component recovery · Synthetic data, configuration (1000, 1000, 1000, 10, 20, 20)joint RRE: 8.9035e − 08 -> 9.78e − 08Hurt
Add nuclear-norm regularization to ℓ1-RJIVEjoint and individual component recovery · Synthetic data, configuration (1000, 1000, 1000, 10, 20, 20)individual RRE: 5.8665e − 08 -> 8.9923e − 08Hurt
Add nuclear-norm regularization to ℓ1-RJIVEjoint and individual component recovery · Synthetic data, configuration (2000, 2000, 2000, 20, 40, 40)individual RRE: 2.3743e − 06 -> 2.0574e − 07Helped
Progress faces using RJIVE rather than original imagesAgeDB age-invariant verification · 5 yearsaccuracy: 0.609 -> 0.637Helped
Progress faces using RJIVE rather than original imagesAgeDB age-invariant verification · 10 yearsaccuracy: 0.591 -> 0.621Helped
Progress faces using RJIVE rather than original imagesAgeDB age-invariant verification · 20 yearsaccuracy: 0.552 -> 0.598Helped

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