Dimensionality Reduction

Dimensionality Reduction of Multimodal Labeled Data by Local Fisher Discriminant Analysis JMLR 2007 Discriminative K-means for Clustering NeurIPS 2007 Euclidean Embedding of Co-occurrence Data JMLR 2007 Graph Laplacians and their Convergence on Random Neighborhood Graphs JMLR 2007 Heterogeneous Component Analysis NeurIPS 2007 Iterative Non-linear Dimensionality Reduction with Manifold Sculpting NeurIPS 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 Predicting Brain States from fMRI Data: Incremental Functional Principal Component Regression NeurIPS 2007 Random Projections for Manifold Learning NeurIPS 2007 Receptive Fields without Spike-Triggering NeurIPS 2007 Sparse Overcomplete Latent Variable Decomposition of Counts Data NeurIPS 2007 Subspace-Based Face Recognition in Analog VLSI NeurIPS 2007 A Kernel Subspace Method by Stochastic Realization for Learning Nonlinear Dynamical Systems NeurIPS 2006 Blind source separation for over-determined delayed mixtures NeurIPS 2006 Computational and Theoretical Analysis of Null Space and Orthogonal Linear Discriminant Analysis JMLR 2006 Conditional Random Sampling: A Sketch-based Sampling Technique for Sparse Data NeurIPS 2006 Convergence of Laplacian Eigenmaps NeurIPS 2006 Denoising and Dimension Reduction in Feature Space NeurIPS 2006 Differential Entropic Clustering of Multivariate Gaussians NeurIPS 2006 Doubly Stochastic Normalization for Spectral Clustering NeurIPS 2006 Emergence of conjunctive visual features by quadratic independent component analysis NeurIPS 2006 Fast Iterative Kernel PCA NeurIPS 2006