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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 301–325 of 796 papers

TitleStatusHype
Estimation of Missing Data in Intelligent Transportation System—0
A new accelerated gradient method inspired by continuous-time perspective—0
Inductive Collaborative Filtering via Relation Graph Learning—0
Matrix Data Deep Decoder - Geometric Learning for Structured Data Completion—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
An Inertial Block Majorization Minimization Framework for Nonsmooth Nonconvex OptimizationCode0
Low-Rank Approximations of Nonseparable Panel Models—0
Optimum Codesign for Image Denoising Between Type-2 Fuzzy Identifier and Matrix Completion Denoiser—0
Fast Convergence of Langevin Dynamics on Manifold: Geodesics meet Log-Sobolev—0
Geometric Matrix Completion: A Functional ViewCode0
DeepVir -- Graphical Deep Matrix Factorization for "In Silico" Antiviral Repositioning: Application to COVID-19Code0
Recent Developments on Factor Models and its Applications in Econometric Learning—0
Meta-learning based Alternating Minimization Algorithm for Non-convex OptimizationCode0
Efficient Model-Based Collaborative Filtering with Fast Adaptive PCACode0
Clustering of Nonnegative Data and an Application to Matrix Completion—0
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