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 1–25 of 796 papers

TitleStatusHype
New Hardness Results for Low-Rank Matrix Completion—0
Contrastive Matrix Completion with Denoising and Augmented Graph Views for Robust RecommendationCode0
N^2: A Unified Python Package and Test Bench for Nearest Neighbor-Based Matrix CompletionCode0
Covariate-Adjusted Deep Causal Learning for Heterogeneous Panel Data Models—0
Optimal Transport with Heterogeneously Missing Data—0
RGNMR: A Gauss-Newton method for robust matrix completion with theoretical guarantees—0
Adaptively-weighted Nearest Neighbors for Matrix CompletionCode0
Euclidean Distance Matrix Completion via Asymmetric Projected Gradient Descent—0
AltGDmin: Alternating GD and Minimization for Partly-Decoupled (Federated) Optimization—0
Truncated Matrix Completion - An Empirical Study—0
Computational Efficient Informative Nonignorable Matrix Completion: A Row- and Column-Wise Matrix U-Statistic Pseudo-Likelihood Approach—0
An extrapolated and provably convergent algorithm for nonlinear matrix decomposition with the ReLU functionCode0
Depth-Aided Color Image Inpainting in Quaternion Domain—0
Fast Two-photon Microscopy by Neuroimaging with Oblong Random Acquisition (NORA)—0
A Linearized Alternating Direction Multiplier Method for Federated Matrix Completion Problems—0
Interference-Aware Edge Runtime Prediction with Conformal Matrix CompletionCode0
Optimal Transfer Learning for Missing Not-at-Random Matrix Completion—0
Recommendations from Sparse Comparison Data: Provably Fast Convergence for Nonconvex Matrix Factorization—0
A Geometric Approach to Personalized Recommendation with Set-Theoretic Constraints Using Box Embeddings—0
Matrix Completion with Graph Information: A Provable Nonconvex Optimization Approach—0
Covariates-Adjusted Mixed-Membership Estimation: A Novel Network Model with Optimal Guarantees—0
Efficient Over-parameterized Matrix Sensing from Noisy Measurements via Alternating Preconditioned Gradient DescentCode0
Norm-Bounded Low-Rank Adaptation—0
Faster Convergence of Riemannian Stochastic Gradient Descent with Increasing Batch Size—0
Matrix Completion in Group Testing: Bounds and Simulations—0
Show:102550
← PrevPage 1 of 32Next →

No leaderboard results yet.