Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Training Invariant Support Vector Machines
Machine Learning
Adjustment Learning and Relevant Component Analysis
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Transformation Invariance in Pattern Recognition-Tangent Distance and Tangent Propagation
Neural Networks: Tricks of the Trade, this book is an outgrowth of a 1996 NIPS workshop
Integrating constraints and metric learning in semi-supervised clustering
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Online and batch learning of pseudo-metrics
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Face Recognition by Using Discriminative Common Vectors
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 1 - Volume 01
Learning Distance Metrics with Contextual Constraints for Image Retrieval
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Computational and Theoretical Analysis of Null Space and Orthogonal Linear Discriminant Analysis
The Journal of Machine Learning Research
Information-theoretic metric learning
Proceedings of the 24th international conference on Machine learning
Structured metric learning for high dimensional problems
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Improving embeddings by flexible exploitation of side information
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
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
Semi-supervised sparse metric learning using alternating linearization optimization
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Coloring local feature extraction
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part II
Discriminative Common Vector Method With Kernels
IEEE Transactions on Neural Networks
Pairwise constraints based multiview features fusion for scene classification
Pattern Recognition
| Hi-index | 0.01 |
We introduce a new algorithm for distance metric learning which uses pairwise similarity (equivalence) and dissimilarity constraints. The method is adapted to the high-dimensional feature spaces that occur in many computer vision applications. It first projects the data onto the subspace orthogonal to the linear span of the difference vectors of similar sample pairs. Similar samples thus have identical projections, i.e., the distance between the two elements of each similar sample pair becomes zero in the projected space. In the projected space we find a linear embedding that maximizes the scatter of the dissimilar sample pairs. This corresponds to a pseudo-metric characterized by a positive semi-definite matrix in the original input space. We also kernelize the method and show that this allows it to handle cases with low-dimensional input spaces and large numbers of similarity constraints. Despite the method's simplicity, experiments on synthetic problems and on real-world image retrieval, visual object classification, gender classification and image segmentation ones demonstrate its effectiveness, yielding significant improvements over the existing distance metric learning methods.