conftrace_

low-rank matrix

174 papers

Explore in graph

Co-occurring keywords

matrix completion (356) convex optimization (1321) matrix factorization (529) low-rank matrix recovery (57) matrix recovery (51) low-rank approximation (323) non-convex optimization (547) nuclear norm (79) gradient descent (1144) collaborative filtering (300)

Papers

Convergence of Gradient Descent with Small Initialization for Unregularized Matrix Completion COLT 2024
The Implicit Bias of Heterogeneity towards Invariance: A Study of Multi-Environment Matrix Sensing NIPS 2024
Learn more, but bother less: parameter efficient continual learning NIPS 2024
Fast Dynamic Sampling for Determinantal Point Processes AISTATS 2024
On Sampling Strategies for Spectral Model Sharding NIPS 2024
Model-free Low-Rank Reinforcement Learning via Leveraged Entry-wise Matrix Estimation NIPS 2024
A Pairwise Pseudo-likelihood Approach for Matrix Completion with Informative Missingness NIPS 2024
A Note on Entrywise Consistency for Mixed-data Matrix Completion JMLR 2024
Coherence-free Entrywise Estimation of Eigenvectors in Low-rank Signal-plus-noise Matrix Models NIPS 2024
Restricted Isometry Property of Rank-One Measurements with Random Unit-Modulus Vectors AISTATS 2024
Absence of spurious solutions far from ground truth: A low-rank analysis with high-order losses AISTATS 2024
Fast and Accurate Estimation of Low-Rank Matrices from Noisy Measurements via Preconditioned Non-Convex Gradient Descent AISTATS 2024
On the Computational and Statistical Complexity of Over-parameterized Matrix Sensing JMLR 2024
Recovering Simultaneously Structured Data via Non-Convex Iteratively Reweighted Least Squares NIPS 2023
Partial Matrix Completion NIPS 2023
Bures-Wasserstein Barycenters and Low-Rank Matrix Recovery AISTATS 2023
Global Convergence of Sub-gradient Method for Robust Matrix Recovery: Small Initialization, Noisy Measurements, and Over-parameterization JMLR 2023
Efficient Robust Principal Component Analysis via Block Krylov Iteration and CUR Decomposition CVPR 2023
Decentralized Matrix Sensing: Statistical Guarantees and Fast Convergence NIPS 2023
Sparse Plus Low Rank Matrix Decomposition: A Discrete Optimization Approach JMLR 2023
Robust High-Dimensional Low-Rank Matrix Estimation: Optimal Rate and Data-Adaptive Tuning JMLR 2023
Near-Optimal Weighted Matrix Completion JMLR 2023
Differentially Private Matrix Completion through Low-rank Matrix Factorization AISTATS 2023
Exponentially Convergent Algorithms for Supervised Matrix Factorization NIPS 2023
Multi-User Reinforcement Learning with Low Rank Rewards ICML 2023