dimensionality reduction

Sparse Kernel Orthonormalized PLS for feature extraction in large data sets NeurIPS 2006 Stratification Learning: Detecting Mixed Density and Dimensionality in High Dimensional Point Clouds NeurIPS 2006 Towards a general independent subspace analysis NeurIPS 2006 Unsupervised Regression with Applications to Nonlinear System Identification NeurIPS 2006 Information Bottleneck for Gaussian Variables JMLR 2005 Learning a Mahalanobis Metric from Equivalence Constraints JMLR 2005 Probabilistic Non-linear Principal Component Analysis with Gaussian Process Latent Variable Models JMLR 2005 Dimensionality Reduction for Supervised Learning with Reproducing Kernel Hilbert Spaces JMLR 2004 Efficient Feature Selection via Analysis of Relevance and Redundancy JMLR 2004 Feature Selection for Unsupervised Learning JMLR 2004 Non-negative Matrix Factorization with Sparseness Constraints JMLR 2004 A Divisive Information-Theoretic Feature Clustering Algorithm for Text Classification JMLR 2003 An Introduction to Variable and Feature Selection JMLR 2003 Dimensionality Reduction via Sparse Support Vector Machines JMLR 2003 Sufficient Dimensionality Reduction JMLR 2003 Think Globally, Fit Locally: Unsupervised Learning of Low Dimensional Manifolds JMLR 2003 Regularized Principal Manifolds JMLR 2001