Binary sparse nonnegative matrix factorization
IEEE Transactions on Circuits and Systems for Video Technology
Transfer Discriminative Logmaps
PCM '09 Proceedings of the 10th Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Biased ISOMap projections for interactive reranking
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Distance approximating dimension reduction of Riemannian manifolds
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Discriminative orthogonal neighborhood-preserving projections for classification
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Constrained Laplacian Eigenmap for dimensionality reduction
Neurocomputing
Biologically inspired feature manifold for gait recognition
Neurocomputing
Entropy controlled Laplacian regularization for least square regression
Signal Processing
Active reranking for web image search
IEEE Transactions on Image Processing
A review of active appearance models
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
A general learning framework using local and global regularization
Pattern Recognition
Discrminative geometry preserving projections
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Evolutionary cross-domain discriminative hessian eigenmaps
IEEE Transactions on Image Processing
Enhanced local texture feature sets for face recognition under difficult lighting conditions
IEEE Transactions on Image Processing
Flexible manifold embedding: a framework for semi-supervised and unsupervised dimension reduction
IEEE Transactions on Image Processing
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Non-goal scene analysis for soccer video
Neurocomputing
A blind watermarking scheme using new nontensor product wavelet filter banks
IEEE Transactions on Image Processing
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
m-SNE: multiview stochastic neighbor embedding
ICONIP'10 Proceedings of the 17th international conference on Neural information processing: theory and algorithms - Volume Part I
Manifold elastic net: a unified framework for sparse dimension reduction
Data Mining and Knowledge Discovery
Orthogonal Complete Discriminant Locality Preserving Projections for Face Recognition
Neural Processing Letters
Transfer latent variable model based on divergence analysis
Pattern Recognition
Manifold learning for visualization of vibrational states of a rotating machine
ICANN'11 Proceedings of the 21st international conference on Artificial neural networks - Volume Part II
Face Recognition Using Kernel UDP
Neural Processing Letters
Social image annotation via cross-domain subspace learning
Multimedia Tools and Applications
A supervised non-linear dimensionality reduction approach for manifold learning
Pattern Recognition
Image-based facial sketch-to-photo synthesis via online coupled dictionary learning
Information Sciences: an International Journal
Interactive cartoon reusing by transfer learning
Signal Processing
Learning colours from textures by sparse manifold embedding
AI'11 Proceedings of the 24th international conference on Advances in Artificial Intelligence
Image classification by multimodal subspace learning
Pattern Recognition Letters
Local CCA alignment and its applications
Neurocomputing
Discriminative information preservation for face recognition
Neurocomputing
Enhanced fisher discriminant criterion for image recognition
Pattern Recognition
A probabilistic model for image representation via multiple patterns
Pattern Recognition
Multi-scale gist feature manifold for building recognition
Neurocomputing
Kernel approximately harmonic projection
Neurocomputing
Kinect image classification using LLC
Proceedings of the 4th International Conference on Internet Multimedia Computing and Service
Joint geometry and variability for image recognition
Neurocomputing
Unsupervised Feature Selection with Feature Clustering
WI-IAT '12 Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Volume 01
Towards the Optimal Discriminant Subspace
WI-IAT '12 Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Volume 01
Local discriminative distance metrics ensemble learning
Pattern Recognition
Correspondence construction for cartoon animation via sparse coding
Proceedings of the Fifth International Conference on Internet Multimedia Computing and Service
Multi-view hypergraph learning by patch alignment framework
Neurocomputing
Robust spectral regression for face recognition
Neurocomputing
G-Optimal Feature Selection with Laplacian regularization
Neurocomputing
Similar handwritten Chinese character recognition by kernel discriminative locality alignment
Pattern Recognition Letters
A Rayleigh-Ritz style method for large-scale discriminant analysis
Pattern Recognition
A Comprehensive Survey to Face Hallucination
International Journal of Computer Vision
Kernel clustering using a hybrid memetic algorithm
Natural Computing: an international journal
Soft label based Linear Discriminant Analysis for image recognition and retrieval
Computer Vision and Image Understanding
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Spectral analysis-based dimensionality reduction algorithms are important and have been popularly applied in data mining and computer vision applications. To date many algorithms have been developed, e.g., principal component analysis, locally linear embedding, Laplacian eigenmaps, and local tangent space alignment. All of these algorithms have been designed intuitively and pragmatically, i.e., on the basis of the experience and knowledge of experts for their own purposes. Therefore, it will be more informative to provide a systematic framework for understanding the common properties and intrinsic difference in different algorithms. In this paper, we propose such a framework, named "patch alignment,” which consists of two stages: part optimization and whole alignment. The framework reveals that 1) algorithms are intrinsically different in the patch optimization stage and 2) all algorithms share an almost identical whole alignment stage. As an application of this framework, we develop a new dimensionality reduction algorithm, termed Discriminative Locality Alignment (DLA), by imposing discriminative information in the part optimization stage. DLA can 1) attack the distribution nonlinearity of measurements; 2) preserve the discriminative ability; and 3) avoid the small-sample-size problem. Thorough empirical studies demonstrate the effectiveness of DLA compared with representative dimensionality reduction algorithms.