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Distance Metric Learning for Large Margin Nearest Neighbor Classification (LMNN) NIPS 2006 Kilian Q. Weinberger, John Blitzer and Lawrence K. Saul.

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Presentation on theme: "Distance Metric Learning for Large Margin Nearest Neighbor Classification (LMNN) NIPS 2006 Kilian Q. Weinberger, John Blitzer and Lawrence K. Saul."— Presentation transcript:

1 Distance Metric Learning for Large Margin Nearest Neighbor Classification (LMNN) NIPS 2006 Kilian Q. Weinberger, John Blitzer and Lawrence K. Saul

2 Problem Distance metric learning for kNN Goal: k-nearest neighbors belong to same class Example from different classes are separated by a large margin kNNLMNN linear classification Linear SVM counterpart

3 Model Mahalanobis distance for metric learning

4 Model Goal: learn the linear transformation L Cost function: Indicates if a target neighbor SVM: Hinge loss

5 How to solve it? Convex optimization with semidefinite programming – The matrix whose elements are linear with the unknown variables is required to be positive semidefinite. Slack variable

6 Classification kNN Energy-based classification

7 Results

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