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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

Near-optimal Differentially Private Principal Components NIPS 2012
Convergence and Energy Landscape for Cheeger Cut Clustering NIPS 2012
Locality Preserving Feature Learning AISTATS 2012
Collaborative Gaussian Processes for Preference Learning NIPS 2012
Semi-supervised Eigenvectors for Locally-biased Learning NIPS 2012
Toward Understanding Complex Spaces: Graph Laplacians on Manifolds with Singularities and Boundaries COLT 2012
Isotropic Hashing NIPS 2012
A Scalable CUR Matrix Decomposition Algorithm: Lower Time Complexity and Tighter Bound NIPS 2012
Nonlinear low-dimensional regression using auxiliary coordinates AISTATS 2012
Statistical Optimization in High Dimensions AISTATS 2012
Local and Global Scaling Reduce Hubs in Space JMLR 2012
Latent Coincidence Analysis: A Hidden Variable Model for Distance Metric Learning NIPS 2012
Factorized Diffusion Map Approximation AISTATS 2012
Learning Sparse Representations of High Dimensional Data on Large Scale Dictionaries NIPS 2011
Mixed-Variate Restricted Boltzmann Machines ACML 2011
Dimensionality Reduction Using the Sparse Linear Model NIPS 2011
Large-Scale Sparse Principal Component Analysis with Application to Text Data NIPS 2011
Unsupervised Multiple Kernel Learning ACML 2011
A Cure for Variance Inflation in High Dimensional Kernel Principal Component Analysis JMLR 2011
Variational Gaussian Process Dynamical Systems NIPS 2011
Directed Graph Embedding: an Algorithm based on Continuous Limits of Laplacian-type Operators NIPS 2011
Learning Anchor Planes for Classification NIPS 2011
Data Skeletonization via Reeb Graphs NIPS 2011
Sparse Features for PCA-Like Linear Regression NIPS 2011
Maximum Covariance Unfolding : Manifold Learning for Bimodal Data NIPS 2011