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Learning Lines with Ordinal Constraints
We study the problem of finding a mapping $f$ from a set of points into the real line, under ordinal triple constraints.
Learning Mahalanobis Metric Spaces via Geometric Approximation Algorithms
Learning Mahalanobis metric spaces is an important problem that has found numerous applications.
Robust Mahalanobis Metric Learning via Geometric Approximation Algorithms
Learning Mahalanobis metric spaces is an important problem that has found numerous applications.
Algorithms for metric learning via contrastive embeddings
We study the problem of supervised learning a metric space under discriminative constraints.
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