Linear Algebra

Optimal Dictionary for Least Squares Representation JMLR 2017 Optimal Shrinkage of Singular Values Under Random Data Contamination NeurIPS 2017 Partitioned Tensor Factorizations for Learning Mixed Membership Models ICML 2017 Rank Determination for Low-Rank Data Completion JMLR 2017 Reconstructing Undirected Graphs from Eigenspaces JMLR 2017 Riemannian Optimization for Skip-Gram Negative Sampling ACL 2017 Robust and Efficient Computation of Eigenvectors in a Generalized Spectral Method for Constrained Clustering AISTATS 2017 SVD-Based Screening for the Graphical Lasso IJCAI 2017 Tensor Biclustering NeurIPS 2017 Tensor Decompositions via Two-Mode Higher-Order SVD (HOSVD) AISTATS 2017 Tensor Decomposition via Simultaneous Power Iteration ICML 2017 Tensor Decomposition with Smoothness ICML 2017 The Unreasonable Effectiveness of Structured Random Orthogonal Embeddings NeurIPS 2017 Unbiased estimates for linear regression via volume sampling NeurIPS 2017 Unified representation of tractography and diffusion-weighted MRI data using sparse multidimensional arrays NeurIPS 2017 An Improved Gap-Dependency Analysis of the Noisy Power Method COLT 2016 A posteriori error bounds for joint matrix decomposition problems NeurIPS 2016 A Subspace Learning Approach for High Dimensional Matrix Decomposition with Efficient Column/Row Sampling ICML 2016 Clustering Signed Networks with the Geometric Mean of Laplacians NeurIPS 2016 Convergence of Stochastic Gradient Descent for PCA ICML 2016 Coordinate-wise Power Method NeurIPS 2016 Correlated-PCA: Principal Components' Analysis when Data and Noise are Correlated NeurIPS 2016 Efficient Algorithms for Large-scale Generalized Eigenvector Computation and Canonical Correlation Analysis ICML 2016 Fast Algorithms for Robust PCA via Gradient Descent NeurIPS 2016 Faster Eigenvector Computation via Shift-and-Invert Preconditioning ICML 2016