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Matrix Completion

Matrix Completion is a method for recovering lost information. It originates from machine learning and usually deals with highly sparse matrices. Missing or unknown data is estimated using the low-rank matrix of the known data.

Source: A Fast Matrix-Completion-Based Approach for Recommendation Systems

Papers

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Showing 276–300 of 796 papers

TitleStatusHype
Forecasting Nonnegative Time Series via Sliding Mask Method (SMM) and Latent Clustered Forecast (LCF)—0
Wasserstein Graph Neural Networks for Graphs with Missing Attributes—0
Matrix Decomposition on Graphs: A Functional View—0
Exact Linear Convergence Rate Analysis for Low-Rank Symmetric Matrix Completion via Gradient Descent—0
Riemannian Perspective on Matrix Factorization—0
Unlabeled Principal Component Analysis and Matrix CompletionCode0
Sparse Array Beamformer Design for Active and Passive Sensing—0
Local Search Algorithms for Rank-Constrained Convex Optimization—0
Estimation of Missing Data in Intelligent Transportation System—0
Matrix Data Deep Decoder - Geometric Learning for Structured Data Completion—0
A new accelerated gradient method inspired by continuous-time perspective—0
Inductive Collaborative Filtering via Relation Graph Learning—0
Outlier-robust sparse/low-rank least-squares regression and robust matrix completionCode0
Deep Learning Approach for Matrix Completion Using Manifold Learning—0
A generalised log-determinant regularizer for online semi-definite programming and its applications—0
Enhancing Parameter-Free Frank Wolfe with an Extra Subproblem—0
Conic Descent and its Application to Memory-efficient Optimization over Positive Semidefinite Matrices—0
Mixed Membership Graph Clustering via Systematic Edge QueryCode0
Non-Local Robust Quaternion Matrix Completion for Color Images and Videos Inpainting—0
Leveraged Matrix Completion with Noise—0
On Using Hamiltonian Monte Carlo Sampling for Reinforcement Learning Problems in High-dimension—0
Sparse Array Beamforming Design for Wideband Signal Models—0
Adversarial Robust Low Rank Matrix Estimation: Compressed Sensing and Matrix Completion—0
Low-Rank Approximations of Nonseparable Panel Models—0
An Inertial Block Majorization Minimization Framework for Nonsmooth Nonconvex OptimizationCode0
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