Dimensionality Reduction

Deflation Methods for Sparse PCA NeurIPS 2008 Diffeomorphic Dimensionality Reduction NeurIPS 2008 Dimensionality Reduction for Data in Multiple Feature Representations NeurIPS 2008 DiscLDA: Discriminative Learning for Dimensionality Reduction and Classification NeurIPS 2008 Extended Grassmann Kernels for Subspace-Based Learning NeurIPS 2008 Gaussian-process factor analysis for low-dimensional single-trial analysis of neural population activity NeurIPS 2008 ICA based on a Smooth Estimation of the Differential Entropy NeurIPS 2008 Kernel Measures of Independence for non-iid Data NeurIPS 2008 Localized Sliced Inverse Regression NeurIPS 2008 Manifold Learning: The Price of Normalization JMLR 2008 One sketch for all: Theory and Application of Conditional Random Sampling NeurIPS 2008 On the Equivalence of Linear Dimensionality-Reducing Transformations JMLR 2008 QUIC-SVD: Fast SVD Using Cosine Trees NeurIPS 2008 Reducing statistical dependencies in natural signals using radial Gaussianization NeurIPS 2008 Robust Kernel Principal Component Analysis NeurIPS 2008 Sparse probabilistic projections NeurIPS 2008 Spectral Hashing NeurIPS 2008 Supervised Exponential Family Principal Component Analysis via Convex Optimization NeurIPS 2008 Theory of matching pursuit NeurIPS 2008 Visualizing Data using t-SNE JMLR 2008 An Analysis of Inference with the Universum NeurIPS 2007 An online Hebbian learning rule that performs Independent Component Analysis NeurIPS 2007 A Unified Near-Optimal Estimator For Dimension Reduction in l_α (0<α≤ 2) Using Stable Random Projections NeurIPS 2007 Bilinear Discriminant Component Analysis JMLR 2007 Colored Maximum Variance Unfolding NeurIPS 2007