SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 551–600 of 796 papers

TitleStatusHype
Online Optimization for Large-Scale Max-Norm Regularization—0
Online Optimization for Max-Norm Regularization—0
Online Policy Learning and Inference by Matrix Completion—0
The Sparse Reverse of Principal Component Analysis for Fast Low-Rank Matrix Completion—0
Online Variational Bayesian Subspace Filtering with Applications—0
Thy Friend is My Friend: Iterative Collaborative Filtering for Sparse Matrix Estimation—0
On Tensor Completion via Nuclear Norm Minimization—0
On the Convergence of Stochastic Gradient Descent with Low-Rank Projections for Convex Low-Rank Matrix Problems—0
On the convex geometry of blind deconvolution and matrix completion—0
On the Fundamental Limits of Matrix Completion: Leveraging Hierarchical Similarity Graphs—0
On the Optimality of Nuclear-norm-based Matrix Completion for Problems with Smooth Non-linear Structure—0
Can Learning Be Explained By Local Optimality In Robust Low-rank Matrix Recovery?—0
On the Power of Adaptivity in Matrix Completion and Approximation—0
On the Power of Truncated SVD for General High-rank Matrix Estimation Problems—0
On the Predictability of Human Assessment: when Matrix Completion Meets NLP Evaluation—0
On the properties of variational approximations of Gibbs posteriors—0
On the simplicity and conditioning of low rank semidefinite programs—0
On the Robustness of Cross-Concentrated Sampling for Matrix Completion—0
Optimal (0,1)-Matrix Completion with Majorization Ordered Objectives (To the memory of Pravin Varaiya)—0
Optimal Exact Matrix Completion Under new Parametrization—0
Optimal Algorithms for Latent Bandits with Cluster Structure—0
Disjunctive Branch-And-Bound for Certifiably Optimal Low-Rank Matrix Completion—0
Optimal Low-Rank Tensor Recovery from Separable Measurements: Four Contractions Suffice—0
Optimal Transfer Learning for Missing Not-at-Random Matrix Completion—0
Optimal Transport with Heterogeneously Missing Data—0
Optimized Waveform Design for OFDM-based ISAC Systems Under Limited Resource Occupancy—0
Optimum Codesign for Image Denoising Between Type-2 Fuzzy Identifier and Matrix Completion Denoiser—0
Orthogonal Inductive Matrix Completion—0
Top-N Recommender System via Matrix Completion—0
Towards Addressing Training Data Scarcity Challenge in Emerging Radio Access Networks: A Survey and Framework—0
PAC-Bayesian matrix completion with a spectral scaled Student prior—0
Parametric Models for Mutual Kernel Matrix Completion—0
Partial Matrix Completion—0
Towards Faster Rates and Oracle Property for Low-Rank Matrix Estimation—0
Penalty Decomposition Methods for Rank Minimization—0
Perturbation Analysis of Randomized SVD and its Applications to Statistics—0
Tracking Completion—0
Phase transitions and sample complexity in Bayes-optimal matrix factorization—0
Poisson Matrix Completion—0
Poisson Matrix Recovery and Completion—0
Wasserstein Graph Neural Networks for Graphs with Missing Attributes—0
Polynomial Matrix Completion for Missing Data Imputation and Transductive Learning—0
Polynomial Precision Dependence Solutions to Alignment Research Center Matrix Completion Problems—0
Power-Flow-Embedded Projection Conic Matrix Completion for Low-Observable Distribution Systems—0
Practical Matrix Completion and Corruption Recovery using Proximal Alternating Robust Subspace Minimization—0
Prediction and Quantification of Individual Athletic Performance—0
Prediction with Unpredictable Feature Evolution—0
Transduction with Matrix Completion: Three Birds with One Stone—0
Preference Completion from Partial Rankings—0
Transduction with Matrix Completion Using Smoothed Rank Function—0
Show:102550
← PrevPage 12 of 16Next →

No leaderboard results yet.