Linear Algebra

Householder Sketch for Accurate and Accelerated Least-Mean-Squares Solvers ICML 2021 Identification of Matrix Joint Block Diagonalization AISTATS 2021 Implicit SVD for Graph Representation Learning NeurIPS 2021 Landscape analysis of an improved power method for tensor decomposition NeurIPS 2021 Learning a mixture of two subspaces over finite fields ALT 2021 Learning Tensor Low-Rank Prior for Hyperspectral Image Reconstruction CVPR 2021 Low-Rank Subspaces in GANs NeurIPS 2021 Low-Rank Tensor Completion by Approximating the Tensor Average Rank ICCV 2021 Mode-wise Tensor Decompositions: Multi-dimensional Generalizations of CUR Decompositions JMLR 2021 Near-Optimal Entrywise Anomaly Detection for Low-Rank Matrices with Sub-Exponential Noise ICML 2021 Near-Optimal Entrywise Sampling of Numerically Sparse Matrices COLT 2021 On Riemannian Optimization over Positive Definite Matrices with the Bures-Wasserstein Geometry NeurIPS 2021 On the Faster Alternating Least-Squares for CCA AISTATS 2021 On the Riemannian Search for Eigenvector Computation JMLR 2021 Optimal Sketching for Trace Estimation NeurIPS 2021 Preconditioned Gradient Descent for Over-Parameterized Nonconvex Matrix Factorization NeurIPS 2021 Principal Bit Analysis: Autoencoding with Schur-Concave Loss ICML 2021 Privately Learning Subspaces NeurIPS 2021 Projection techniques to update the truncated SVD of evolving matrices with applications ICML 2021 Ranking and synchronization from pairwise measurements via SVD JMLR 2021 Reduced-Rank Regression with Operator Norm Error COLT 2021 Regularized spectral methods for clustering signed networks JMLR 2021 Reproducing kernel Hilbert C*-module and kernel mean embeddings JMLR 2021 Revisiting Co-Occurring Directions: Sharper Analysis and Efficient Algorithm for Sparse Matrices AAAI 2021 Single Pass Entrywise-Transformed Low Rank Approximation ICML 2021