Pages that link to "Item:Q2290334"
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The following pages link to Supervised distance metric learning through maximization of the Jeffrey divergence (Q2290334):
Displaying 12 items.
- A boosting approach for supervised Mahalanobis distance metric learning (Q645912) (← links)
- Fast generalization rates for distance metric learning. Improved theoretical analysis for smooth strongly convex distance metric learning (Q669277) (← links)
- Survey on distance metric learning and dimensionality reduction in data mining (Q1711231) (← links)
- Ordinal regression with explainable distance metric learning based on ordered sequences (Q2071504) (← links)
- A nearest-neighbor search model for distance metric learning (Q2123495) (← links)
- An efficient method for clustered multi-metric learning (Q2200672) (← links)
- The analysis from nonlinear distance metric to kernel-based prescription prediction system (Q3383188) (← links)
- A multi-birth metric learning framework based on binary constraints (Q6052417) (← links)
- \(\mathrm{OPM^2L}\): an optimal instance partition-based multi-metric learning method for heterogeneous dataset classification (Q6052667) (← links)
- A fast diagonal distance metric learning approach for large-scale datasets (Q6092062) (← links)
- Optimal reach estimation and metric learning (Q6136583) (← links)
- Physics-constrained non-Gaussian probabilistic learning on manifolds (Q6495601) (← links)
