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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 251–300 of 796 papers

TitleStatusHype
Matrix Completion with Model-free Weighting—0
A Pre-training Oracle for Predicting Distances in Social Networks—0
A Scalable Second Order Method for Ill-Conditioned Matrix Completion from Few SamplesCode1
Patch Tracking-based Streaming Tensor Ring Completion for Visual Data Recovery—0
Multi-source Learning via Completion of Block-wise Overlapping Noisy Matrices—0
Low-Rank Hankel Tensor Completion for Traffic Speed EstimationCode0
Scalable and Explainable 1-Bit Matrix Completion via Graph Signal LearningCode1
Sharp Restricted Isometry Property Bounds for Low-rank Matrix Recovery Problems with Corrupted Measurements—0
Deep learned SVT: Unrolling singular value thresholding to obtain better MSE—0
On the Optimality of Nuclear-norm-based Matrix Completion for Problems with Smooth Non-linear Structure—0
Nonparametric Trace Regression in High Dimensions via Sign Series Representation—0
Implicit Regularization in Deep Tensor Factorization—0
Matrix completion based on Gaussian parameterized belief propagation—0
Multi-target prediction for dummies using two-branch neural networks—0
NoisyCUR: An algorithm for two-cost budgeted matrix completionCode0
PAC-Bayesian Matrix Completion with a Spectral Scaled Student Prior—0
Deep Permutation Equivariant Structure from MotionCode1
Joint Matrix Completion and Compressed Sensing for State Estimation in Low-observable Distribution System—0
Adversarially-Trained Nonnegative Matrix FactorizationCode0
Simulation comparisons between Bayesian and de-biased estimators in low-rank matrix completionCode0
A Neural Network for SemigroupsCode0
Structure-Preserving Progressive Low-rank Image Completion for Defending Adversarial Attacks—0
Progresses and Challenges in Link Prediction—0
Implicit Regularization in Tensor FactorizationCode0
Policy Augmentation: An Exploration Strategy for Faster Convergence of Deep Reinforcement Learning AlgorithmsCode0
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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