Research map / Learning theory and algorithms / Matrix and tensor methods
Trace Quotient Meets Sparsity: A Method for Learning Low Dimensional Image Representations
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Jointly learn a sparse dictionary and low-dimensional projection using trace quotient optimization | PCA-SparLow · USPS | 1NN accuracy: 86.36% -> 92.18% | Helped |
| Jointly learn a sparse dictionary and low-dimensional projection using trace quotient optimization | PCA-SparLow · MNIST | 1NN accuracy: 83.43% -> 89.42% | Helped |
| Add dictionary coherence and initialization-dictionary regularizers (ablation) | PCA-SparLow · USPS | 1NN accuracy | Helped |
| Add dictionary coherence and initialization-dictionary regularizers (ablation) | PCA-SparLow · USPS | reconstruction PSNR | Helped |
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