Linear Algebra

Convolutional Imputation of Matrix Networks ICML 2018 Differentially Private Robust Low-Rank Approximation NeurIPS 2018 DS*: Tighter Lifting-Free Convex Relaxations for Quadratic Matching Problems CVPR 2018 Efficient coordinate-wise leading eigenvector computation ALT 2018 Fast Randomized PCA for Sparse Data ACML 2018 Gradient Descent Meets Shift-and-Invert Preconditioning for Eigenvector Computation NeurIPS 2018 High Dimensional Linear Regression using Lattice Basis Reduction NeurIPS 2018 High-Order Co-Clustering via Strictly Orthogonal and Symmetric L1-Norm Nonnegative Matrix Tri-Factorization IJCAI 2018 How Much Restricted Isometry is Needed In Nonconvex Matrix Recovery? NeurIPS 2018 Learning in Reproducing Kernel Kreı̆n Spaces ICML 2018 Leveraging Well-Conditioned Bases: Streaming and Distributed Summaries in Minkowski p-Norms ICML 2018 Low-Rank Riemannian Optimization on Positive Semidefinite Stochastic Matrices with Applications to Graph Clustering ICML 2018 Low-Rank Tucker Decomposition of Large Tensors Using TensorSketch NeurIPS 2018 Near Optimal Frequent Directions for Sketching Dense and Sparse Matrices ICML 2018 On Binary Embedding using Circulant Matrices JMLR 2018 On Truly Block Eigensolvers via Riemannian Optimization AISTATS 2018 Provably Correct Algorithms for Matrix Column Subset Selection with Selectively Sampled Data JMLR 2018 Relating Leverage Scores and Density using Regularized Christoffel Functions NeurIPS 2018 Reverse Iterative Volume Sampling for Linear Regression JMLR 2018 Robust Subspace Approximation in a Stream NeurIPS 2018 Rotation Averaging and Strong Duality CVPR 2018 Smoothed Analysis of Discrete Tensor Decomposition and Assemblies of Neurons NeurIPS 2018 Stochastic Chebyshev Gradient Descent for Spectral Optimization NeurIPS 2018 Sublinear Time Low-Rank Approximation of Distance Matrices NeurIPS 2018 Subspace Embedding and Linear Regression with Orlicz Norm ICML 2018