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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

Showing 376400 of 796 papers

TitleStatusHype
Graph Sampling for Matrix Completion Using Recurrent Gershgorin Disc Shift0
Matrix Completion, Counterfactuals, and Factor Analysis of Missing Data0
New and Explicit Constructions of Unbalanced Ramanujan Bipartite Graphs0
The Sparse Reverse of Principal Component Analysis for Fast Low-Rank Matrix Completion0
Deep geometric matrix completion: Are we doing it right?0
Statistical Inferences of Linear Forms for Noisy Matrix Completion0
Scalable Probabilistic Matrix Factorization with Graph-Based PriorsCode0
Deterministic Completion of Rectangular Matrices Using Asymmetric Ramanujan Graphs: Exact and Stable Recovery0
Scalable Bayesian Non-linear Matrix Completion0
Deep Non-Rigid Structure from Motion with Missing Data0
Collaborative Filtering and Multi-Label Classification with Matrix Factorization0
The Landscape of Non-convex Empirical Risk with Degenerate Population Risk0
Low-rank matrix completion and denoising under Poisson noise0
A divide-and-conquer algorithm for binary matrix completion0
Depth Restoration: A fast low-rank matrix completion via dual-graph regularization0
Approximate matrix completion based on cavity method0
Online Variational Bayesian Subspace Filtering with Applications0
Generalization error bounds for kernel matrix completion and extrapolation0
Online Matrix Completion with Side Information0
Efficiently escaping saddle points on manifolds0
Inference and Uncertainty Quantification for Noisy Matrix Completion0
Graphon Estimation from Partially Observed Network DataCode0
Guaranteed Matrix Completion Under Multiple Linear Transformations0
Implicit Regularization in Deep Matrix FactorizationCode0
Spectral Perturbation Meets Incomplete Multi-view Data0
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