dimensionality reduction

Landmarking Manifolds with Gaussian Processes ICML 2015 Learning Concept Embeddings With Combined Human-Machine Expertise ICCV 2015 Linear Dimensionality Reduction: Survey, Insights, and Generalizations JMLR 2015 Local High-Order Regularization on Data Manifolds CVPR 2015 Majorization-Minimization for Manifold Embedding AISTATS 2015 Online PCA with Spectral Bounds COLT 2015 On the consistency theory of high dimensional variable screening NeurIPS 2015 Principal Geodesic Analysis for Probability Measures under the Optimal Transport Metric NeurIPS 2015 Probabilistic Curve Learning: Coulomb Repulsion and the Electrostatic Gaussian Process NeurIPS 2015 Projection Bank: From High-Dimensional Data to Medium-Length Binary Codes ICCV 2015 Projection Metric Learning on Grassmann Manifold With Application to Video Based Face Recognition CVPR 2015 Robust Principal Component Analysis on Graphs ICCV 2015 Semi-Supervised Learning With Explicit Relationship Regularization CVPR 2015 Space-Time Local Embeddings NeurIPS 2015 Sparse PCA via Bipartite Matchings NeurIPS 2015 Sparse Projections for High-Dimensional Binary Codes CVPR 2015 Stay on path: PCA along graph paths ICML 2015 Streaming Sparse Principal Component Analysis ICML 2015 Structured Feature Selection ICCV 2015 Sufficient Dimension Reduction via Direct Estimation of the Gradients of Logarithmic Conditional Densities ACML 2015 Theory of Dual-sparse Regularized Randomized Reduction ICML 2015 Understanding and Evaluating Sparse Linear Discriminant Analysis AISTATS 2015 Unsupervised Simultaneous Orthogonal Basis Clustering Feature Selection CVPR 2015 Accelerating t-SNE using Tree-Based Algorithms JMLR 2014 A Compact and Discriminative Face Track Descriptor CVPR 2014