Dimensionality Reduction

Sparse PCA via Covariance Thresholding NeurIPS 2014 Sparse PCA with Oracle Property NeurIPS 2014 Sparsity on Statistical Simplexes and Diversity in Social Ranking ACML 2014 Square Deal: Lower Bounds and Improved Relaxations for Tensor Recovery ICML 2014 Subspace Clustering for Sequential Data CVPR 2014 Subspace Embeddings for the Polynomial Kernel NeurIPS 2014 The Noisy Power Method: A Meta Algorithm with Applications NeurIPS 2014 Tight convex relaxations for sparse matrix factorization NeurIPS 2014 Tighten after Relax: Minimax-Optimal Sparse PCA in Polynomial Time NeurIPS 2014 Uniqueness of Ordinal Embedding COLT 2014 Zeta Hull Pursuits: Learning Nonconvex Data Hulls NeurIPS 2014 A Joint Intensity and Depth Co-sparse Analysis Model for Depth Map Super-resolution ICCV 2013 Algorithms and Hardness for Robust Subspace Recovery COLT 2013 Analytic Bilinear Appearance Subspace Construction for Modeling Image Irradiance under Natural Illumination and Non-Lambertian Reflectance CVPR 2013 A Near-Optimal Algorithm for Differentially-Private Principal Components JMLR 2013 A Scalable Unsupervised Feature Merging Approach to Efficient Dimensionality Reduction of High-Dimensional Visual Data ICCV 2013 Bayesian inference for low rank spatiotemporal neural receptive fields NeurIPS 2013 Blind Signal Separation in the Presence of Gaussian Noise COLT 2013 Canonical Correlation Analysis based on Hilbert-Schmidt Independence Criterion and Centered Kernel Target Alignment ICML 2013 Cluster Trees on Manifolds NeurIPS 2013 Complexity Theoretic Lower Bounds for Sparse Principal Component Detection COLT 2013 Dense Non-rigid Point-Matching Using Random Projections CVPR 2013 Dictionary Learning and Sparse Coding on Grassmann Manifolds: An Extrinsic Solution ICCV 2013 Efficient Learning of Simplices COLT 2013 Efficient Multi-label Classification with Many Labels ICML 2013