low-rank matrix recovery

Fast and Accurate Estimation of Low-Rank Matrices from Noisy Measurements via Preconditioned Non-Convex Gradient Descent AISTATS 2024 LERE: Learning-Based Low-Rank Matrix Recovery with Rank Estimation AAAI 2024 On the Computational and Statistical Complexity of Over-parameterized Matrix Sensing JMLR 2024 Restricted Isometry Property of Rank-One Measurements with Random Unit-Modulus Vectors AISTATS 2024 Bures-Wasserstein Barycenters and Low-Rank Matrix Recovery AISTATS 2023 Faster Projection-Free Augmented Lagrangian Methods via Weak Proximal Oracle AISTATS 2023 Global Convergence of Sub-gradient Method for Robust Matrix Recovery: Small Initialization, Noisy Measurements, and Over-parameterization JMLR 2023 Implicit Balancing and Regularization: Generalization and Convergence Guarantees for Overparameterized Asymmetric Matrix Sensing COLT 2023 Low-rank matrix recovery with unknown correspondence UAI 2023 Fundamental limits for rank-one matrix estimation with groupwise heteroskedasticity AISTATS 2022 Local and Global Linear Convergence of General Low-Rank Matrix Recovery Problems AAAI 2022 Projected Robust PCA with Application to Smooth Image Recovery JMLR 2022 Sharp Restricted Isometry Property Bounds for Low-Rank Matrix Recovery Problems with Corrupted Measurements AAAI 2022 Adaptive Rank Estimate in Robust Principal Component Analysis CVPR 2021 Learned Robust PCA: A Scalable Deep Unfolding Approach for High-Dimensional Outlier Detection NeurIPS 2021 On the Absence of Spurious Local Minima in Nonlinear Low-Rank Matrix Recovery Problems AISTATS 2021 Rank Overspecified Robust Matrix Recovery: Subgradient Method and Exact Recovery NeurIPS 2021 Square Root Principal Component Pursuit: Tuning-Free Noisy Robust Matrix Recovery NeurIPS 2021 How many samples is a good initial point worth in Low-rank Matrix Recovery? NeurIPS 2020 On the Convergence of Stochastic Gradient Descent with Low-Rank Projections for Convex Low-Rank Matrix Problems COLT 2020 Robust Low-Rank Discovery of Data-Driven Partial Differential Equations AAAI 2020 Robust Recovery via Implicit Bias of Discrepant Learning Rates for Double Over-parameterization NeurIPS 2020 Factor Group-Sparse Regularization for Efficient Low-Rank Matrix Recovery NeurIPS 2019 Low-Rank Tensor Completion With a New Tensor Nuclear Norm Induced by Invertible Linear Transforms CVPR 2019 Nonconvex Matrix Factorization from Rank-One Measurements AISTATS 2019