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Large margin nearest neighbor

Known as: LMNN, Large margin nearest neighbor classification 
Large margin nearest neighbor (LMNN) classification is a statistical machine learning algorithm for metric learning. It learns a pseudometric… Expand
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Papers overview

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2017
2017
We introduce a novel supervised metric learning algorithm named parameter free large margin nearest neighbor (PFLMNN) which can… Expand
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2013
2013
The accuracy of the k-nearest neighbor algorithm depends on the distance function used to measure similarity between instances… Expand
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Highly Cited
2011
Highly Cited
2011
Nearest neighbor (NN) classifier with dynamic time warping (DTW) is considered to be an effective method for time series… Expand
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2011
2011
We concern the problem of learning a Mahalanobis distance metric for improving nearest neighbor classification. Our work is built… Expand
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2011
2011
The nearest neighbor classification is a simple and yet effective technique for pattern recognition. Performance of this… Expand
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Highly Cited
2010
Highly Cited
2010
Multi-task learning (MTL) improves the prediction performance on multiple, different but related, learning problems through… Expand
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2010
2010
Distance metric learning has exhibited its great power to enhance performance in metric related pattern recognition tasks. The… Expand
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Highly Cited
2009
Highly Cited
2009
We study boosting algorithms for learning to rank. We give a general margin-based bound for ranking based on covering numbers for… Expand
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Highly Cited
2005
Highly Cited
2005
The accuracy of k-nearest neighbor (kNN) classification depends significantly on the metric used to compute distances between… Expand
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Highly Cited
1992
Highly Cited
1992
A training algorithm that maximizes the margin between the training patterns and the decision boundary is presented. The… Expand
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