Dimensionality Reduction

On the Sample Complexity of Subspace Learning NeurIPS 2013 Parallel Vector Field Embedding JMLR 2013 Pass-efficient unsupervised feature selection NeurIPS 2013 Principal Component Analysis on non-Gaussian Dependent Data ICML 2013 Probabilistic Principal Geodesic Analysis NeurIPS 2013 Provable Subspace Clustering: When LRR meets SSC NeurIPS 2013 Randomized partition trees for exact nearest neighbor search COLT 2013 Recovering the Optimal Solution by Dual Random Projection COLT 2013 Robust learning of low-dimensional dynamics from large neural ensembles NeurIPS 2013 Robust Low Rank Kernel Embeddings of Multivariate Distributions NeurIPS 2013 Robust Sparse Principal Component Regression under the High Dimensional Elliptical Model NeurIPS 2013 Robust Transfer Principal Component Analysis with Rank Constraints NeurIPS 2013 Robust Tucker Tensor Decomposition for Effective Image Representation ICCV 2013 Scalable Optimization of Neighbor Embedding for Visualization ICML 2013 Scalable Sparse Subspace Clustering CVPR 2013 Sign Cauchy Projections and Chi-Square Kernel NeurIPS 2013 Simultaneous Rectification and Alignment via Robust Recovery of Low-rank Tensors NeurIPS 2013 Sparse Additive Text Models with Low Rank Background NeurIPS 2013 Sparse Principal Component Analysis for High Dimensional Multivariate Time Series AISTATS 2013 Sparse Subspace Denoising for Image Manifolds CVPR 2013 Sparse Uncorrelated Linear Discriminant Analysis ICML 2013 Speeding up Permutation Testing in Neuroimaging NeurIPS 2013 Stochastic Optimization of PCA with Capped MSG NeurIPS 2013 Stress Functions for Nonlinear Dimension Reduction, Proximity Analysis, and Graph Drawing JMLR 2013 The Fast Convergence of Incremental PCA NeurIPS 2013