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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 1–50 of 796 papers

TitleStatusHype
Efficient Minimum Bayes Risk Decoding using Low-Rank Matrix Completion AlgorithmsCode2
AIR-Net: Adaptive and Implicit Regularization Neural Network for Matrix CompletionCode1
Adaptive and Implicit Regularization for Matrix CompletionCode1
Teaching Arithmetic to Small TransformersCode1
Matrix Completion with Quantified Uncertainty through Low Rank Gaussian CopulaCode1
A Scalable Second Order Method for Ill-Conditioned Matrix Completion from Few SamplesCode1
Escaping Saddle Points in Ill-Conditioned Matrix Completion with a Scalable Second Order MethodCode1
Towards Open-World Recommendation: An Inductive Model-based Collaborative Filtering ApproachCode1
Sensing Theorems for Unsupervised Learning in Linear Inverse ProblemsCode1
Simultaneous imputation and disease classification in incomplete medical datasets using Multigraph Geometric Matrix Completion (MGMC)Code1
Compressible Dynamics in Deep Overparameterized Low-Rank Learning & AdaptationCode1
Causal Matrix CompletionCode1
Linear Recursive Feature Machines provably recover low-rank matricesCode1
Inductive Matrix Completion Based on Graph Neural NetworksCode1
Graph Convolutional Matrix CompletionCode1
GLocal-K: Global and Local Kernels for Recommender SystemsCode1
Indiscriminate Poisoning Attacks on Unsupervised Contrastive LearningCode1
Inductive Matrix Completion Using Graph AutoencoderCode1
Matrix Completion and Low-Rank SVD via Fast Alternating Least SquaresCode1
OBOE: Collaborative Filtering for AutoML Model SelectionCode1
Scalable and Explainable 1-Bit Matrix Completion via Graph Signal LearningCode1
Simple, Fast, and Flexible Framework for Matrix Completion with Infinite Width Neural NetworksCode1
Crosslingual Topic Modeling with WikiPDACode1
Compressed sensing of low-rank plus sparse matricesCode1
Adversarial Crowdsourcing Through Robust Rank-One Matrix CompletionCode1
SAVOIAS: A Diverse, Multi-Category Visual Complexity DatasetCode1
Deep Permutation Equivariant Structure from MotionCode1
Randomized Approach to Matrix Completion: Applications in Collaborative Filtering and Image InpaintingCode1
Detecting and Tracking Small and Dense Moving Objects in Satellite Videos: A BenchmarkCode1
Accelerating Ill-Conditioned Low-Rank Matrix Estimation via Scaled Gradient DescentCode1
k-Space Deep Learning for Accelerated MRICode1
Deep Generalization of Structured Low-Rank Algorithms (Deep-SLR)Code1
Generalized Low Rank ModelsCode1
Geometric Matrix Completion with Recurrent Multi-Graph Neural NetworksCode1
Hyperparameter optimization in deep multi-target predictionCode1
Dictionary Learning for Massive Matrix FactorizationCode0
Distant Supervision for Relation Extraction with Matrix CompletionCode0
DeepVir -- Graphical Deep Matrix Factorization for "In Silico" Antiviral Repositioning: Application to COVID-19Code0
Depth Image Inpainting: Improving Low Rank Matrix Completion with Low Gradient RegularizationCode0
Distributional Matrix Completion via Nearest Neighbors in the Wasserstein SpaceCode0
Adversarially-Trained Nonnegative Matrix FactorizationCode0
Graphon Estimation from Partially Observed Network DataCode0
Deep Collective Matrix Factorization for Augmented Multi-View LearningCode0
Accelerating SGD for Highly Ill-Conditioned Huge-Scale Online Matrix CompletionCode0
Decomposition into Low-rank plus Additive Matrices for Background/Foreground Separation: A Review for a Comparative Evaluation with a Large-Scale DatasetCode0
Spectral Geometric Matrix CompletionCode0
Deep Models of Interactions Across SetsCode0
Doubly robust nearest neighbors in factor modelsCode0
Collective Matrix CompletionCode0
CayleyNets: Graph Convolutional Neural Networks with Complex Rational Spectral FiltersCode0
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