low-rank approximation

LR-GLM: High-Dimensional Bayesian Inference Using Low-Rank Data Approximations ICML 2019 Manifold denoising by Nonlinear Robust Principal Component Analysis NeurIPS 2019 Model-free Nonconvex Matrix Completion: Local Minima Analysis and Applications in Memory-efficient Kernel PCA JMLR 2019 Non-Local Meets Global: An Integrated Paradigm for Hyperspectral Denoising CVPR 2019 Online High Rank Matrix Completion CVPR 2019 Optimal Analysis of Subset-Selection Based L_p Low-Rank Approximation NeurIPS 2019 Optimal Sketching for Kronecker Product Regression and Low Rank Approximation NeurIPS 2019 Outlier-Robust Multi-Aspect Streaming Tensor Completion and Factorization IJCAI 2019 PowerSGD: Practical Low-Rank Gradient Compression for Distributed Optimization NeurIPS 2019 Provable Non-linear Inductive Matrix Completion NeurIPS 2019 RaFM: Rank-Aware Factorization Machines ICML 2019 Regularized Weighted Low Rank Approximation NeurIPS 2019 Relative Error Bound Analysis for Nuclear Norm Regularized Matrix Completion JMLR 2019 Sample-Optimal Low-Rank Approximation of Distance Matrices COLT 2019 Scalable Kernel K-Means Clustering with Nystrom Approximation: Relative-Error Bounds JMLR 2019 Scalable Learning in Reproducing Kernel Krein Spaces ICML 2019 Spatial Aggregation Facilitates Discovery of Spatial Topics ACL 2019 Sublinear Time Numerical Linear Algebra for Structured Matrices AAAI 2019 Total Least Squares Regression in Input Sparsity Time NeurIPS 2019 Towards a Zero-One Law for Column Subset Selection NeurIPS 2019 A Dual Framework for Low-rank Tensor Completion NeurIPS 2018 Deep Non-Blind Deconvolution via Generalized Low-Rank Approximation NeurIPS 2018 Differentially Private Robust Low-Rank Approximation NeurIPS 2018 Efficient Convex Completion of Coupled Tensors using Coupled Nuclear Norms NeurIPS 2018 FastGRNN: A Fast, Accurate, Stable and Tiny Kilobyte Sized Gated Recurrent Neural Network NeurIPS 2018