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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 751–796 of 796 papers

TitleStatusHype
Bayesian Graph Convolutional Neural Networks Using Non-Parametric Graph Learning—0
Bayesian Learning for Low-Rank matrix reconstruction—0
Bayesian Low-rank Matrix Completion with Dual-graph Embedding: Prior Analysis and Tuning-free Inference—0
Bayesian matrix completion: prior specification—0
Social Trust Prediction via Max-norm Constrained 1-bit Matrix Completion—0
PAC-Bayesian Matrix Completion with a Spectral Scaled Student Prior—0
Multi-source Learning via Completion of Block-wise Overlapping Noisy Matrices—0
Binary Matrix Completion Using Unobserved Entries—0
Binary matrix completion with nonconvex regularizers—0
Blind Regression: Nonparametric Regression for Latent Variable Models via Collaborative Filtering—0
BlockEcho: Retaining Long-Range Dependencies for Imputing Block-Wise Missing Data—0
Blocked Collaborative Bandits: Online Collaborative Filtering with Per-Item Budget Constraints—0
Boolean Matrix Factorization and Noisy Completion via Message Passing—0
Bounded Manifold Completion—0
Solving Cold Start Problem in Recommendation with Attribute Graph Neural Networks—0
Spectal Harmonics: Bridging Spectral Embedding and Matrix Completion in Self-Supervised Learning—0
Calibrated Elastic Regularization in Matrix Completion—0
Fixing Inventory Inaccuracies At Scale—0
Categorical Matrix Completion—0
Causal Imputation for Counterfactual SCMs: Bridging Graphs and Latent Factor Models—0
Causal Inference with Corrupted Data: Measurement Error, Missing Values, Discretization, and Differential Privacy—0
Solving the Robust Matrix Completion Problem via a System of Nonlinear Equations—0
A Linearized Alternating Direction Multiplier Method for Federated Matrix Completion Problems—0
Solving Uncalibrated Photometric Stereo Using Fewer Images by Jointly Optimizing Low-rank Matrix Completion and Integrability—0
CAYLEYNETS: SPECTRAL GRAPH CNNS WITH COMPLEX RATIONAL FILTERS—0
Characterization of the equivalence of robustification and regularization in linear and matrix regression—0
Clipped Matrix Completion: A Remedy for Ceiling Effects—0
Cluster Developing 1-Bit Matrix Completion—0
Clustering of Nonnegative Data and an Application to Matrix Completion—0
Coherence and sufficient sampling densities for reconstruction in compressed sensing—0
Collaborative Automotive Radar Sensing via Mixed-Precision Distributed Array Completion—0
Collaborative Filtering and Multi-Label Classification with Matrix Factorization—0
Collaborative Filtering in a Non-Uniform World: Learning with the Weighted Trace Norm—0
Unorganized Malicious Attacks Detection—0
Collaborative Self-Attention for Recommender Systems—0
SP2: A Second Order Stochastic Polyak Method—0
Color Image Inpainting via Robust Pure Quaternion Matrix Completion: Error Bound and Weighted Loss—0
Color Image Recovery Using Generalized Matrix Completion over Higher-Order Finite Dimensional Algebra—0
Column _2,0-norm regularized factorization model of low-rank matrix recovery and its computation—0
Combining Explicit and Implicit Regularization for Efficient Learning in Deep Networks—0
Communication Efficient Parallel Algorithms for Optimization on Manifolds—0
Communication-Efficient Projection-Free Algorithm for Distributed Optimization—0
Community Detection and Matrix Completion with Social and Item Similarity Graphs—0
Completing Any Low-rank Matrix, Provably—0
Completing Low-Rank Matrices with Corrupted Samples from Few Coefficients in General Basis—0
Algebraic-Combinatorial Methods for Low-Rank Matrix Completion with Application to Athletic Performance Prediction—0
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