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Low-Rank Matrix Completion

Low-Rank Matrix Completion is an important problem with several applications in areas such as recommendation systems, sketching, and quantum tomography. The goal in matrix completion is to recover a low rank matrix, given a small number of entries of the matrix.

Source: Universal Matrix Completion

Papers

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Showing 1–50 of 158 papers

TitleStatusHype
Efficient Minimum Bayes Risk Decoding using Low-Rank Matrix Completion AlgorithmsCode2
Compressible Dynamics in Deep Overparameterized Low-Rank Learning & AdaptationCode1
Randomized Approach to Matrix Completion: Applications in Collaborative Filtering and Image InpaintingCode1
Linear Recursive Feature Machines provably recover low-rank matricesCode1
Teaching Arithmetic to Small TransformersCode1
Guaranteed Tensor Recovery Fused Low-rankness and SmoothnessCode1
Generalized Nonconvex Approach for Low-Tubal-Rank Tensor RecoveryCode1
A Scalable Second Order Method for Ill-Conditioned Matrix Completion from Few SamplesCode1
Escaping Saddle Points in Ill-Conditioned Matrix Completion with a Scalable Second Order MethodCode1
Deep Generalization of Structured Low-Rank Algorithms (Deep-SLR)Code1
New Hardness Results for Low-Rank Matrix Completion—0
AltGDmin: Alternating GD and Minimization for Partly-Decoupled (Federated) Optimization—0
Truncated Matrix Completion - An Empirical Study—0
Norm-Bounded Low-Rank Adaptation—0
Faster Convergence of Riemannian Stochastic Gradient Descent with Increasing Batch Size—0
Low rank matrix completion and realization of graphs: results and problems—0
A privacy-preserving distributed credible evidence fusion algorithm for collective decision-making—0
Efficient and Robust Freeway Traffic Speed Estimation under Oblique Grid using Vehicle Trajectory DataCode0
Abrupt Learning in Transformers: A Case Study on Matrix Completion—0
Riemannian Optimization for Non-convex Euclidean Distance Geometry with Global Recovery Guarantees—0
Decentralized Singular Value Decomposition for Large-scale Distributed Sensor Networks—0
Online Matrix Completion: A Collaborative Approach with Hott Items—0
Leave-One-Out Analysis for Nonconvex Robust Matrix Completion with General Thresholding Functions—0
Generalized Low-Rank Matrix Completion Model with Overlapping Group Error Representation—0
Nonconvex Federated Learning on Compact Smooth Submanifolds With Heterogeneous Data—0
Symmetric Matrix Completion with ReLU Sampling—0
Efficient Federated Low Rank Matrix Completion—0
Discrete Aware Matrix Completion via Convexized _0-Norm Approximation—0
Entry-Specific Bounds for Low-Rank Matrix Completion under Highly Non-Uniform Sampling—0
Effect of Beampattern on Matrix Completion with Sparse Arrays—0
Harmonic Retrieval Using Weighted Lifted-Structure Low-Rank Matrix Completion—0
Efficient Compression of Overparameterized Deep Models through Low-Dimensional Learning DynamicsCode0
A framework to generate sparsity-inducing regularizers for enhanced low-rank matrix completion—0
Robust Low-Rank Matrix Completion via a New Sparsity-Inducing Regularizer—0
Matrix Completion in Almost-Verification Time—0
Data-based system representations from irregularly measured data—0
Non-Convex Optimizations for Machine Learning with Theoretical Guarantee: Robust Matrix Completion and Neural Network Learning—0
Graph-Based Matrix Completion Applied to Weather Data—0
Efficient Alternating Minimization with Applications to Weighted Low Rank Approximation—0
Matrix Completion from General Deterministic Sampling Patterns—0
Spectal Harmonics: Bridging Spectral Embedding and Matrix Completion in Self-Supervised Learning—0
Disjunctive Branch-And-Bound for Certifiably Optimal Low-Rank Matrix Completion—0
A Majorization-Minimization Gauss-Newton Method for 1-Bit Matrix Completion—0
Low Rank Matrix Completion via Robust Alternating Minimization in Nearly Linear Time—0
Learning Transition Operators From Sparse Space-Time Samples—0
Low-Rank Covariance Completion for Graph Quilting with Applications to Functional Connectivity—0
Online Low Rank Matrix Completion—0
Introducing the Huber mechanism for differentially private low-rank matrix completion—0
Robust Matrix Completion with Heavy-tailed Noise—0
Bayesian Low-rank Matrix Completion with Dual-graph Embedding: Prior Analysis and Tuning-free Inference—0
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