Linear Algebra

Fast recovery from a union of subspaces NeurIPS 2016 Fast Stochastic Algorithms for SVD and PCA: Convergence Properties and Convexity ICML 2016 Generating Gestural Scores from Acoustics Through a Sparse Anchor-Based Representation of Speech Interspeech 2016 Global Optimality of Local Search for Low Rank Matrix Recovery NeurIPS 2016 How to Fake Multiply by a Gaussian Matrix ICML 2016 LazySVD: Even Faster SVD Decomposition Yet Without Agonizing Pain NeurIPS 2016 Learning from Multiway Data: Simple and Efficient Tensor Regression ICML 2016 Learning HMMs with Nonparametric Emissions via Spectral Decompositions of Continuous Matrices NeurIPS 2016 Linear Shape Deformation Models With Local Support Using Graph-Based Structured Matrix Factorisation CVPR 2016 Low-Rank Approximation of Weighted Tree Automata AISTATS 2016 Low-Rank Doubly Stochastic Matrix Decomposition for Cluster Analysis JMLR 2016 Low-Rank Regression with Tensor Responses NeurIPS 2016 Low-rank Solutions of Linear Matrix Equations via Procrustes Flow ICML 2016 Matrix Eigen-decomposition via Doubly Stochastic Riemannian Optimization ICML 2016 Multiresolution Matrix Compression AISTATS 2016 Non-Gaussian Component Analysis with Log-Density Gradient Estimation AISTATS 2016 Normalized Spectral Map Synchronization NeurIPS 2016 Orthogonal Random Features NeurIPS 2016 Principal Component Projection Without Principal Component Analysis ICML 2016 Quadratic Optimization with Orthogonality Constraints: Explicit Lojasiewicz Exponent and Linear Convergence of Line-Search Methods ICML 2016 Recovery Guarantee of Non-negative Matrix Factorization via Alternating Updates NeurIPS 2016 Revisiting the Nyström Method for Improved Large-scale Machine Learning JMLR 2016 Robust Spectral Detection of Global Structures in the Data by Learning a Regularization NeurIPS 2016 Single Pass PCA of Matrix Products NeurIPS 2016 SPSD Matrix Approximation vis Column Selection: Theories, Algorithms, and Extensions JMLR 2016