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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 51–100 of 158 papers

TitleStatusHype
Fixed-rank matrix factorizations and Riemannian low-rank optimization—0
Fusion Subspace Clustering: Full and Incomplete Data—0
Generalized Low-Rank Matrix Completion Model with Overlapping Group Error Representation—0
Graph-Based Matrix Completion Applied to Weather Data—0
Guaranteed Matrix Completion Under Multiple Linear Transformations—0
Harmonic Retrieval Using Weighted Lifted-Structure Low-Rank Matrix Completion—0
High Dimensional Statistical Estimation under Uniformly Dithered One-bit Quantization—0
High-Rank Matrix Completion and Clustering under Self-Expressive Models—0
Implicit Regularization in Nonconvex Statistical Estimation: Gradient Descent Converges Linearly for Phase Retrieval, Matrix Completion, and Blind Deconvolution—0
Implicit Regularization in Nonconvex Statistical Estimation: Gradient Descent Converges Linearly for Phase Retrieval and Matrix Completion—0
Introducing the Huber mechanism for differentially private low-rank matrix completion—0
Learning Latent Features with Pairwise Penalties in Low-Rank Matrix Completion—0
Learning Transition Operators From Sparse Space-Time Samples—0
Leave-One-Out Analysis for Nonconvex Robust Matrix Completion with General Thresholding Functions—0
Simple Heuristics Yield Provable Algorithms for Masked Low-Rank Approximation—0
Low-Rank Covariance Completion for Graph Quilting with Applications to Functional Connectivity—0
Low-rank matrix completion and denoising under Poisson noise—0
Low rank matrix completion and realization of graphs: results and problems—0
Low Rank Matrix Completion via Robust Alternating Minimization in Nearly Linear Time—0
Low Rank Matrix Completion with Exponential Family Noise—0
Low-rank optimization with trace norm penalty—0
Low-tubal-rank Tensor Completion using Alternating Minimization—0
Manopt, a Matlab toolbox for optimization on manifolds—0
Matrix Completion from General Deterministic Sampling Patterns—0
Matrix Completion from Power-Law Distributed Samples—0
Matrix Completion in Almost-Verification Time—0
Modelling Competitive Sports: Bradley-Terry-Élő Models for Supervised and On-Line Learning of Paired Competition Outcomes—0
Nearly-optimal Robust Matrix Completion—0
Nearly Optimal Robust Matrix Completion—0
New Hardness Results for Low-Rank Matrix Completion—0
Noisy Matrix Completion: Understanding Statistical Guarantees for Convex Relaxation via Nonconvex Optimization—0
Nonconvex Federated Learning on Compact Smooth Submanifolds With Heterogeneous Data—0
Non-Convex Optimizations for Machine Learning with Theoretical Guarantee: Robust Matrix Completion and Neural Network Learning—0
Norm-Bounded Low-Rank Adaptation—0
Novel Structured Low-rank algorithm to recover spatially smooth exponential image time series—0
Nuclear norm penalization and optimal rates for noisy low rank matrix completion—0
Obtaining error-minimizing estimates and universal entry-wise error bounds for low-rank matrix completion—0
On Deterministic Sampling Patterns for Robust Low-Rank Matrix Completion—0
Online Low Rank Matrix Completion—0
Online Matrix Completion: A Collaborative Approach with Hott Items—0
Online Matrix Completion and Online Robust PCA—0
Disjunctive Branch-And-Bound for Certifiably Optimal Low-Rank Matrix Completion—0
Optimum Codesign for Image Denoising Between Type-2 Fuzzy Identifier and Matrix Completion Denoiser—0
Phase transitions and sample complexity in Bayes-optimal matrix factorization—0
Practical Matrix Completion and Corruption Recovery using Proximal Alternating Robust Subspace Minimization—0
Probabilistic low-rank matrix completion on finite alphabets—0
Probabilistic Low-Rank Matrix Completion with Adaptive Spectral Regularization Algorithms—0
R3MC: A Riemannian three-factor algorithm for low-rank matrix completion—0
Ranking Recovery from Limited Comparisons using Low-Rank Matrix Completion—0
Reconstruction of Fragmented Trajectories of Collective Motion using Hadamard Deep Autoencoders—0
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