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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 401425 of 796 papers

TitleStatusHype
Matrix Completion in the Unit Hypercube via Structured Matrix FactorizationCode0
Sum-of-squares meets square loss: Fast rates for agnostic tensor completion0
STAR-GCN: Stacked and Reconstructed Graph Convolutional Networks for Recommender SystemsCode0
Collaborative Self-Attention for Recommender Systems0
Prediction with Unpredictable Feature Evolution0
Gradient Descent for Sparse Rank-One Matrix Completion for Crowd-Sourced Aggregation of Sparsely Interacting Workers0
Adaptive Matrix Completion for the Users and the Items in TailCode0
Simple Heuristics Yield Provable Algorithms for Masked Low-Rank Approximation0
Low-rank matrix recovery with composite optimization: good conditioning and rapid convergence0
On Low-rank Trace Regression under General Sampling DistributionCode0
Matrix Completion With Selective Sampling0
Binary matrix completion with nonconvex regularizers0
Multi-View Matrix Completion for Multi-Label Image Classification0
Cluster Developing 1-Bit Matrix Completion0
Machine Learning Methods Economists Should Know About0
Ensemble Methods for Causal Effects in Panel Data Settings0
State-Building through Public Land Disposal? An Application of Matrix Completion for Counterfactual PredictionCode0
InceptionGCN: Receptive Field Aware Graph Convolutional Network for Disease Prediction0
Provable Tensor Ring CompletionCode0
Matrix Completion via Nonconvex Regularization: Convergence of the Proximal Gradient AlgorithmCode0
On the convex geometry of blind deconvolution and matrix completion0
Multispectral snapshot demosaicing via non-convex matrix completion0
Noisy Matrix Completion: Understanding Statistical Guarantees for Convex Relaxation via Nonconvex Optimization0
Provable Low Rank Phase RetrievalCode0
Robust Matrix Completion State Estimation in Distribution Systems0
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