Discriminant Adaptive Nearest Neighbor Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Evaluation of Statistical Approaches to Text Categorization
Information Retrieval
SVM binary classifier ensembles for image classification
Proceedings of the tenth international conference on Information and knowledge management
Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Laplacian Eigenmaps for dimensionality reduction and data representation
Neural Computation
Think globally, fit locally: unsupervised learning of low dimensional manifolds
The Journal of Machine Learning Research
Learning from User Behavior in Image Retrieval: Application of Market Basket Analysis
International Journal of Computer Vision - Special Issue on Content-Based Image Retrieval
Convex Optimization
Online and batch learning of pseudo-metrics
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Manifold-ranking based image retrieval
Proceedings of the 12th annual ACM international conference on Multimedia
Applying Neighborhood Consistency for Fast Clustering and Kernel Density Estimation
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Learning a semantic space from user's relevance feedback for image retrieval
IEEE Transactions on Circuits and Systems for Video Technology
Learning to combine distances for complex representations
Proceedings of the 24th international conference on Machine learning
Nonlinear adaptive distance metric learning for clustering
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
BoostCluster: boosting clustering by pairwise constraints
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Learning a Mahalanobis distance metric for data clustering and classification
Pattern Recognition
Human Activity Recognition with Metric Learning
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
Hierarchical Classifiers for Complex Spatio-temporal Concepts
Transactions on Rough Sets IX
Emerging Trends in Visual Computing
Category detection using hierarchical mean shift
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Accuracy of distance metric learning algorithms
Proceedings of the 2nd Workshop on Data Mining using Matrices and Tensors
Large margin nearest local mean classifier
Signal Processing
Semantics-preserving bag-of-words models for efficient image annotation
LS-MMRM '09 Proceedings of the First ACM workshop on Large-scale multimedia retrieval and mining
Distance metric learning from uncertain side information with application to automated photo tagging
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Unified video annotation via multigraph learning
IEEE Transactions on Circuits and Systems for Video Technology
Beyond distance measurement: constructing neighborhood similarity for video annotation
IEEE Transactions on Multimedia - Special section on communities and media computing
Hierarchical Multi-view Fisher Discriminant Analysis
ICONIP '09 Proceedings of the 16th International Conference on Neural Information Processing: Part II
A unified framework of subspace and distance metric learning for face recognition
AMFG'07 Proceedings of the 3rd international conference on Analysis and modeling of faces and gestures
Generalized iterative RELIEF for supervised distance metric learning
Pattern Recognition
Joint learning of labels and distance metric
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on game theory
Semi-supervised distance metric learning for collaborative image retrieval and clustering
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Semantics-preserving bag-of-words models and applications
IEEE Transactions on Image Processing
Distance metric learning from uncertain side information for automated photo tagging
ACM Transactions on Intelligent Systems and Technology (TIST)
Mining social images with distance metric learning for automated image tagging
Proceedings of the fourth ACM international conference on Web search and data mining
A multi-scale learning framework for visual categorization
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part I
Matching 2D and 3D articulated shapes using the eccentricity transform
Computer Vision and Image Understanding
A novel two-level nearest neighbor classification algorithm using an adaptive distance metric
Knowledge-Based Systems
Fast neighborhood component analysis
Neurocomputing
Multiview Metric Learning with Global Consistency and Local Smoothness
ACM Transactions on Intelligent Systems and Technology (TIST)
The dissimilarity representation for structural pattern recognition
CIARP'11 Proceedings of the 16th Iberoamerican Congress conference on Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
A boosting approach for supervised Mahalanobis distance metric learning
Pattern Recognition
Learning image-to-class distance metric for image classification
ACM Transactions on Intelligent Systems and Technology (TIST) - Special section on agent communication, trust in multiagent systems, intelligent tutoring and coaching systems
Local discriminative distance metrics ensemble learning
Pattern Recognition
Learning bilinear model for matching queries and documents
The Journal of Machine Learning Research
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Learning application-specific distance metrics from labeled data is critical for both statistical classification and information retrieval. Most of the earlier work in this area has focused on finding metrics that simultaneously optimize compactness and separability in a global sense. Specifically, such distance metrics attempt to keep all of the data points in each class close together while ensuring that data points from different classes are separated. However, particularly when classes exhibit multimodal data distributions, these goals conflict and thus cannot be simultaneously satisfied. This paper proposes a Local Distance Metric (LDM) that aims to optimize local compactness and local separability. We present an efficient algorithm that employs eigenvector analysis, and bound optimization to learn the LDM from training data in a probabilistic framework. We demonstrate that LDM achieves significant improvements in both classification and retrieval accuracy compared to global distance learning and kernel-based KNN.