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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 76–100 of 158 papers

TitleStatusHype
Faster Convergence of Riemannian Stochastic Gradient Descent with Increasing Batch Size—0
Fast Low-Rank Bayesian Matrix Completion with Hierarchical Gaussian Prior Models—0
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
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