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 1–25 of 796 papers

Title	Date	Tasks	Status	Hype	Score
Efficient Minimum Bayes Risk Decoding using Low-Rank Matrix Completion Algorithms	Jun 5, 2024	Low-Rank Matrix CompletionMachine Translation	CodeCode Available	2	5
k-Space Deep Learning for Accelerated MRI	May 10, 2018	compressed sensingDeep Learning	CodeCode Available	1	5
Adaptive and Implicit Regularization for Matrix Completion	Aug 11, 2022	Matrix Completion	CodeCode Available	1	5
Generalized Low Rank Models	Oct 1, 2014	ClusteringDenoising	CodeCode Available	1	5
Indiscriminate Poisoning Attacks on Unsupervised Contrastive Learning	Feb 22, 2022	Contrastive LearningData Augmentation	CodeCode Available	1	5
Towards Open-World Recommendation: An Inductive Model-based Collaborative Filtering Approach	Jul 9, 2020	Collaborative FilteringMatrix Completion	CodeCode Available	1	5
Compressed sensing of low-rank plus sparse matrices	Jul 18, 2020	compressed sensingMatrix Completion	CodeCode Available	1	5
Crosslingual Topic Modeling with WikiPDA	Sep 23, 2020	ArticlesMatrix Completion	CodeCode Available	1	5
Deep Permutation Equivariant Structure from Motion	Apr 14, 2021	Matrix Completion	CodeCode Available	1	5
Escaping Saddle Points in Ill-Conditioned Matrix Completion with a Scalable Second Order Method	Sep 7, 2020	Low-Rank Matrix CompletionMatrix Completion	CodeCode Available	1	5
Graph Convolutional Matrix Completion	Jun 7, 2017	Collaborative FilteringLink Prediction	CodeCode Available	1	5
Hyperparameter optimization in deep multi-target prediction	Nov 8, 2022	AutoMLBenchmarking	CodeCode Available	1	5
Inductive Matrix Completion Based on Graph Neural Networks	Apr 26, 2019	Graph Neural NetworkMatrix Completion	CodeCode Available	1	5
Inductive Matrix Completion Using Graph Autoencoder	Aug 25, 2021	Graph Neural NetworkMatrix Completion	CodeCode Available	1	5
Deep Generalization of Structured Low-Rank Algorithms (Deep-SLR)	Dec 7, 2019	Computational EfficiencyImage Reconstruction	CodeCode Available	1	5
Causal Matrix Completion	Sep 30, 2021	Matrix CompletionRecommendation Systems	CodeCode Available	1	5
Adversarial Crowdsourcing Through Robust Rank-One Matrix Completion	Oct 23, 2020	Matrix Completion	CodeCode Available	1	5
Compressible Dynamics in Deep Overparameterized Low-Rank Learning & Adaptation	Jun 6, 2024	Language ModellingLow-Rank Matrix Completion	CodeCode Available	1	5
Accelerating Ill-Conditioned Low-Rank Matrix Estimation via Scaled Gradient Descent	May 18, 2020	Matrix Completion	CodeCode Available	1	5
AIR-Net: Adaptive and Implicit Regularization Neural Network for Matrix Completion	Oct 12, 2021	Matrix CompletionMissing Elements	CodeCode Available	1	5
Detecting and Tracking Small and Dense Moving Objects in Satellite Videos: A Benchmark	Nov 25, 2021	Matrix CompletionMoving Object Detection	CodeCode Available	1	5
Geometric Matrix Completion with Recurrent Multi-Graph Neural Networks	Apr 22, 2017	Collaborative FilteringMatrix Completion	CodeCode Available	1	5
A Scalable Second Order Method for Ill-Conditioned Matrix Completion from Few Samples	Jun 3, 2021	Low-Rank Matrix CompletionMatrix Completion	CodeCode Available	1	5
GLocal-K: Global and Local Kernels for Recommender Systems	Aug 27, 2021	Collaborative FilteringMatrix Completion	CodeCode Available	1	5
Linear Recursive Feature Machines provably recover low-rank matrices	Jan 9, 2024	Dimensionality ReductionLow-Rank Matrix Completion	CodeCode Available	1	5

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