dimensionality reduction

720 papers

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Also known as

SDR PCA DR

Co-occurring keywords

manifold learning (402) principal component analysis (316) feature extraction (1578) random projection (145) unsupervised learning (3255) representation learning (6174) kernel methods (1096) metric learning (1189) feature selection (649) matrix factorization (529)

Papers

Sparse Kernel Orthonormalized PLS for feature extraction in large data sets NIPS 2006

Learning to Traverse Image Manifolds NIPS 2006

Unsupervised Regression with Applications to Nonlinear System Identification NIPS 2006

Manifold Denoising NIPS 2006

Stratification Learning: Detecting Mixed Density and Dimensionality in High Dimensional Point Clouds NIPS 2006

Towards a general independent subspace analysis NIPS 2006

Gaussian and Wishart Hyperkernels NIPS 2006

In Search of Non-Gaussian Components of a High-Dimensional Distribution JMLR 2006

Information Bottleneck for Gaussian Variables JMLR 2005

Probabilistic Non-linear Principal Component Analysis with Gaussian Process Latent Variable Models JMLR 2005

Learning a Mahalanobis Metric from Equivalence Constraints JMLR 2005

Non-negative Matrix Factorization with Sparseness Constraints JMLR 2004

Efficient Feature Selection via Analysis of Relevance and Redundancy JMLR 2004

Feature Selection for Unsupervised Learning JMLR 2004

Think Globally, Fit Locally: Unsupervised Learning of Low Dimensional Manifolds JMLR 2003

A Divisive Information-Theoretic Feature Clustering Algorithm for Text Classification JMLR 2003

Sufficient Dimensionality Reduction JMLR 2003

Dimensionality Reduction via Sparse Support Vector Machines JMLR 2003

An Introduction to Variable and Feature Selection JMLR 2003

Regularized Principal Manifolds JMLR 2001