matrix sensing

Finding the Signal in the Spam: Jointly Learning Rewards and Worker Reliability from Pairwise Comparisons UAI 2026 Fast Non-convex Matrix Sensing with Optimal Sample Complexity UAI 2025 Non-convex matrix sensing: Breaking the quadratic rank barrier in the sample complexity Extended Abstract COLT 2025 Absence of spurious solutions far from ground truth: A low-rank analysis with high-order losses AISTATS 2024 A General Algorithm for Solving Rank-one Matrix Sensing AISTATS 2024 Alternating minimization for generalized rank one matrix sensing: Sharp predictions from a random initialization ALT 2024 Fast and Accurate Estimation of Low-Rank Matrices from Noisy Measurements via Preconditioned Non-Convex Gradient Descent AISTATS 2024 Globally Q-linear Gauss-Newton Method for Overparameterized Non-convex Matrix Sensing NeurIPS 2024 How Over-Parameterization Slows Down Gradient Descent in Matrix Sensing: The Curses of Symmetry and Initialization ICLR 2024 The Implicit Bias of Heterogeneity towards Invariance: A Study of Multi-Environment Matrix Sensing NeurIPS 2024 Algorithmic Regularization in Tensor Optimization: Towards a Lifted Approach in Matrix Sensing NeurIPS 2023 Decentralized Matrix Sensing: Statistical Guarantees and Fast Convergence NeurIPS 2023 Geometric Analysis of Matrix Sensing over Graphs NeurIPS 2023 Greedy Pruning with Group Lasso Provably Generalizes for Matrix Sensing NeurIPS 2023 Implicit Balancing and Regularization: Generalization and Convergence Guarantees for Overparameterized Asymmetric Matrix Sensing COLT 2023 Noisy Low-rank Matrix Optimization: Geometry of Local Minima and Convergence Rate AISTATS 2023 Robust Matrix Sensing in the Semi-Random Model NeurIPS 2023 Semidefinite Programming versus Burer-Monteiro Factorization for Matrix Sensing AAAI 2023 Understanding Incremental Learning of Gradient Descent: A Fine-grained Analysis of Matrix Sensing ICML 2023 Implicit Regularization in Matrix Sensing via Mirror Descent NeurIPS 2021 Rank Overspecified Robust Matrix Recovery: Subgradient Method and Exact Recovery NeurIPS 2021 Implicit regularization for deep neural networks driven by an Ornstein-Uhlenbeck like process COLT 2020 Low-rank regularization and solution uniqueness in over-parameterized matrix sensing AISTATS 2020 The Landscape of Non-convex Empirical Risk with Degenerate Population Risk NeurIPS 2019 Non-square matrix sensing without spurious local minima via the Burer-Monteiro approach AISTATS 2017