Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Database for Handwritten Text Recognition Research
IEEE Transactions on Pattern Analysis and Machine Intelligence
Laplacian Eigenmaps for dimensionality reduction and data representation
Neural Computation
Component-Based Face Recognition with 3D Morphable Models
CVPRW '04 Proceedings of the 2004 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'04) Volume 5 - Volume 05
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Recognition Using Laplacianfaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
Local Discriminant Embedding and Its Variants
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Neighborhood Preserving Embedding
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Graph Embedding and Extensions: A General Framework for Dimensionality Reduction
IEEE Transactions on Pattern Analysis and Machine Intelligence
An efficient face verification method in a transformed domain
Pattern Recognition Letters
Dimensionality Reduction of Multimodal Labeled Data by Local Fisher Discriminant Analysis
The Journal of Machine Learning Research
IEEE Transactions on Computers
IEEE Transactions on Pattern Analysis and Machine Intelligence
Orthogonal neighborhood preserving discriminant analysis for face recognition
Pattern Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
A least squares formulation for canonical correlation analysis
Proceedings of the 25th international conference on Machine learning
Hypergraph spectral learning for multi-label classification
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Fitting a graph to vector data
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Graph construction and b-matching for semi-supervised learning
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Sparsity preserving projections with applications to face recognition
Pattern Recognition
Locality sensitive discriminant analysis
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
IEEE Transactions on Neural Networks
Semi-supervised metric learning using pairwise constraints
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Face recognition using discriminant locality preserving projections
Image and Vision Computing
Sparsity preserving discriminant analysis for single training image face recognition
Pattern Recognition Letters
Graph-optimized locality preserving projections
Pattern Recognition
Bagging Constraint Score for feature selection with pairwise constraints
Pattern Recognition
A scalable two-stage approach for a class of dimensionality reduction techniques
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
LPP solution schemes for use with face recognition
Pattern Recognition
Data Fitting and Uncertainty: A Practical Introduction to Weighted Least Squares and Beyond
Data Fitting and Uncertainty: A Practical Introduction to Weighted Least Squares and Beyond
Supervised optimal locality preserving projection
Pattern Recognition
Graph optimization for dimensionality reduction with sparsity constraints
Pattern Recognition
A Multiple Maximum Scatter Difference Discriminant Criterion for Facial Feature Extraction
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Efficient and robust feature extraction by maximum margin criterion
IEEE Transactions on Neural Networks
Expert Systems with Applications: An International Journal
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A Constrained large Margin Local Projection (CMLP) technique for multimodal dimensionality reduction is proposed. We elaborate the criterion of CMLP from a pairwise constrained marginal perspective. Four effective CMLP solution schemes are presented and the corresponding comparative analyses are given. An equivalent weighted least squares formulation for CMLP is also detailed. CMLP is originated from the criterion of Locality Preserving Projections (LPP), but CMLP offers a number of attractive advantages over LPP. To keep the intrinsic proximity relations of inter-class and intra-class similarity pairs, the localized pairwise Cannot-Link and Must-Link constraints are applied to specify the types of those neighboring pairs. By utilizing the CMLP criterion, margins between inter- and intra-class clusters are significantly enlarged. As a result, multimodal distributions are effectively preserved. To further optimize the CMLP criterion, one feasible improvement strategy is described. With kernel methods, we present the kernelized extensions of our approaches. Mathematical comparisons and analyses between this work and the related works are also detailed. Extensive simulations including multivariate manifold visualization and classification on the benchmark UCL, ORL, YALE, UMIST, MIT CBCL and USPS datasets are conducted to verify the efficiency of our techniques. The presented results reveal that our methods are highly competitive with and even outperform some widely used state-of-the-art algorithms.