dimensionality reduction

Dimensionality Reduction of Multimodal Labeled Data by Local Fisher Discriminant Analysis JMLR 2007 Dimensionality Reduction Using Automatic Supervision for Vision-Based Terrain Learning RSS 2007 Euclidean Embedding of Co-occurrence Data JMLR 2007 Iterative Non-linear Dimensionality Reduction with Manifold Sculpting NeurIPS 2007 Learning omnidirectional path following using dimensionality reduction RSS 2007 Learning the 2-D Topology of Images NeurIPS 2007 Learning the structure of manifolds using random projections NeurIPS 2007 Locality and low-dimensions in the prediction of natural experience from fMRI NeurIPS 2007 People Tracking with the Laplacian Eigenmaps Latent Variable Model NeurIPS 2007 Random Projections for Manifold Learning NeurIPS 2007 Subspace-Based Face Recognition in Analog VLSI NeurIPS 2007 Computational and Theoretical Analysis of Null Space and Orthogonal Linear Discriminant Analysis JMLR 2006 Convergence of Laplacian Eigenmaps NeurIPS 2006 Denoising and Dimension Reduction in Feature Space NeurIPS 2006 Fast Iterative Kernel PCA NeurIPS 2006 Gaussian and Wishart Hyperkernels NeurIPS 2006 Graph Laplacian Regularization for Large-Scale Semidefinite Programming NeurIPS 2006 In-Network PCA and Anomaly Detection NeurIPS 2006 In Search of Non-Gaussian Components of a High-Dimensional Distribution JMLR 2006 Large Margin Component Analysis NeurIPS 2006 Learning to Traverse Image Manifolds NeurIPS 2006 Manifold Denoising NeurIPS 2006 MLLE: Modified Locally Linear Embedding Using Multiple Weights NeurIPS 2006 Nonnegative Sparse PCA NeurIPS 2006 Randomized PCA Algorithms with Regret Bounds that are Logarithmic in the Dimension NeurIPS 2006