Nonlinear component analysis as a kernel eigenvalue problem
Neural Computation
Learning a kernel matrix for nonlinear dimensionality reduction
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Principal Manifolds and Nonlinear Dimensionality Reduction via Tangent Space Alignment
SIAM Journal on Scientific Computing
An Improved Cluster Labeling Method for Support Vector Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Large Margin Methods for Structured and Interdependent Output Variables
The Journal of Machine Learning Research
Neighborhood Preserving Embedding
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Experimental Study on Pedestrian Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Dynamic Characterization of Cluster Structures for Robust and Inductive Support Vector Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Learning to Localize Objects with Structured Output Regression
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
Cutting-plane training of structural SVMs
Machine Learning
Constructing sparse kernel machines using attractors
IEEE Transactions on Neural Networks
Fast support-based clustering method for large-scale problems
Pattern Recognition
Manifold learning-based feature transformation for phone classification
NOLISP'07 Proceedings of the 2007 international conference on Advances in nonlinear speech processing
Dynamic Dissimilarity Measure for Support-Based Clustering
IEEE Transactions on Knowledge and Data Engineering
Inferring 3D body pose from silhouettes using activity manifold learning
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Image-Based Human Age Estimation by Manifold Learning and Locally Adjusted Robust Regression
IEEE Transactions on Image Processing
Active set support vector regression
IEEE Transactions on Neural Networks
Reduced Support Vector Machines: A Statistical Theory
IEEE Transactions on Neural Networks
Support vector machines training data selection using a genetic algorithm
SSPR'12/SPR'12 Proceedings of the 2012 Joint IAPR international conference on Structural, Syntactic, and Statistical Pattern Recognition
Randomized Sampling for Large Data Applications of SVM
ICMLA '12 Proceedings of the 2012 11th International Conference on Machine Learning and Applications - Volume 01
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Most manifold learning techniques are used to transform high-dimensional data sets into low-dimensional space. In the use of such techniques, after unseen data samples are added to the data set, retraining is usually necessary. However, retraining is a time-consuming process and no guarantee of the transformation into the exactly same coordinates, thus presenting a barrier to the application of manifold learning as a preprocessing step in predictive modeling. To solve this problem, learning a mapping from high-dimensional representations to low-dimensional coordinates is proposed via structured support vector machine. After training a mapping, low-dimensional representations of unobserved data samples can be easily predicted. Experiments on several datasets show that the proposed method outperforms the existing out-of-sample extension methods.