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cs.LG2021
Hierarchical Subspace Learning for Dimensionality Reduction to Improve Classification Accuracy in Large Data Sets
Parisa Abdolrahim Poorheravi, Vincent Gaudet
Manifold learning is used for dimensionality reduction, with the goal of finding a projection subspace to increase and decrease the inter- and intraclass variances, respectively. H…
cs.LG2020
Acceleration of Large Margin Metric Learning for Nearest Neighbor Classification Using Triplet Mining and Stratified Sampling
Parisa Abdolrahim Poorheravi, Benyamin Ghojogh, Vincent Gaudet +2
Metric learning is one of the techniques in manifold learning with the goal of finding a projection subspace for increasing and decreasing the inter- and intra-class variances, res…