dimensionality reduction

STDP enables spiking neurons to detect hidden causes of their inputs NeurIPS 2009 Toward Provably Correct Feature Selection in Arbitrary Domains NeurIPS 2009 Bayesian Exponential Family PCA NeurIPS 2008 Convergence and Rate of Convergence of a Manifold-Based Dimension Reduction Algorithm NeurIPS 2008 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 Manifold Learning: The Price of Normalization JMLR 2008 One sketch for all: Theory and Application of Conditional Random Sampling NeurIPS 2008 On Relevant Dimensions in Kernel Feature Spaces JMLR 2008 QUIC-SVD: Fast SVD Using Cosine Trees NeurIPS 2008 Randomized Online PCA Algorithms with Regret Bounds that are Logarithmic in the Dimension JMLR 2008 Reducing statistical dependencies in natural signals using radial Gaussianization NeurIPS 2008 Robust Kernel Principal Component Analysis NeurIPS 2008 Supervised Exponential Family Principal Component Analysis via Convex Optimization 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 Compressed Regression NeurIPS 2007