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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 126–150 of 158 papers

TitleStatusHype
Ranking Recovery from Limited Comparisons using Low-Rank Matrix Completion—0
Reconstruction of Fragmented Trajectories of Collective Motion using Hadamard Deep Autoencoders—0
Recovery of damped exponentials using structured low rank matrix completion—0
Reflection Removal Using Low-Rank Matrix Completion—0
Relaxed Leverage Sampling for Low-rank Matrix Completion—0
Reproducing Kernel Hilbert Space, Mercer's Theorem, Eigenfunctions, Nyström Method, and Use of Kernels in Machine Learning: Tutorial and Survey—0
Riemannian Optimization for Non-convex Euclidean Distance Geometry with Global Recovery Guarantees—0
Riemannian Stochastic Proximal Gradient Methods for Nonsmooth Optimization over the Stiefel Manifold—0
Riemannian stochastic quasi-Newton algorithm with variance reduction and its convergence analysis—0
Robust Low-rank Matrix Completion via an Alternating Manifold Proximal Gradient Continuation Method—0
Robust Low-Rank Matrix Completion via a New Sparsity-Inducing Regularizer—0
Robust Matrix Completion with Heavy-tailed Noise—0
RTRMC: A Riemannian trust-region method for low-rank matrix completion—0
Scaled Gradients on Grassmann Manifolds for Matrix Completion—0
Scaled stochastic gradient descent for low-rank matrix completion—0
Secrets of Matrix Factorization: Approximations, Numerics, Manifold Optimization and Random Restarts—0
Efficient Compression of Overparameterized Deep Models through Low-Dimensional Learning DynamicsCode0
Guaranteed Rank Minimization via Singular Value ProjectionCode0
Depth Image Inpainting: Improving Low Rank Matrix Completion with Low Gradient RegularizationCode0
Riemannian stochastic variance reduced gradient algorithm with retraction and vector transportCode0
Efficient and Robust Freeway Traffic Speed Estimation under Oblique Grid using Vehicle Trajectory DataCode0
Algebraic Variety Models for High-Rank Matrix CompletionCode0
Mixed Membership Graph Clustering via Systematic Edge QueryCode0
A Gradient Descent Algorithm on the Grassman Manifold for Matrix CompletionCode0
Adaptive Matrix Completion for the Users and the Items in TailCode0
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