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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 151–200 of 796 papers

TitleStatusHype
Optimal Algorithms for Latent Bandits with Cluster Structure—0
Quantizing Heavy-tailed Data in Statistical Estimation: (Near) Minimax Rates, Covariate Quantization, and Uniform Recovery—0
Rank-1 Matrix Completion with Gradient Descent and Small Random Initialization—0
Generalization Bounds for Inductive Matrix Completion in Low-noise Settings—0
Conditions for Estimation of Sensitivities of Voltage Magnitudes to Complex Power InjectionsCode0
Learning Transition Operators From Sparse Space-Time Samples—0
Doubly robust nearest neighbors in factor models—0
Multiple Imputation with Neural Network Gaussian Process for High-dimensional Incomplete DataCode0
Efficient Rigid Body Localization based on Euclidean Distance Matrix Completion for AGV Positioning under Harsh Environment—0
Low Rank Quaternion Matrix Completion Based on Quaternion QR Decomposition and Sparse Regularizer—0
Always Valid Risk Monitoring for Online Matrix Completion—0
A Generalized Latent Factor Model Approach to Mixed-data Matrix Completion with Entrywise ConsistencyCode0
Hyperparameter optimization in deep multi-target predictionCode1
Deep Linear Networks for Matrix Completion -- An Infinite Depth Limit—0
Graph Regularized Probabilistic Matrix Factorization for Drug-Drug Interactions Prediction—0
A Sequence-Aware Recommendation Method Based on Complex Networks—0
Bounded Simplex-Structured Matrix Factorization: Algorithms, Identifiability and ApplicationsCode0
Low-Rank Covariance Completion for Graph Quilting with Applications to Functional Connectivity—0
Inductive Matrix Completion and Root-MUSIC-Based Channel Estimation for Intelligent Reflecting Surface (IRS)-Aided Hybrid MIMO Systems—0
Synthesis of Sparse Linear Arrays via Low-Rank Hankel Matrix Completion—0
SUPER-Rec: SUrrounding Position-Enhanced Representation for Recommendation—0
Optimal (0,1)-Matrix Completion with Majorization Ordered Objectives (To the memory of Pravin Varaiya)—0
Online Low Rank Matrix Completion—0
Recursive Gaussian Process over graphs for Integrating Multi-timescale Measurements in Low-Observable Distribution Systems—0
Partial Matrix Completion—0
Accelerating SGD for Highly Ill-Conditioned Huge-Scale Online Matrix CompletionCode0
Matrix Completion with Cross-Concentrated Sampling: Bridging Uniform Sampling and CUR SamplingCode0
A Novel Plug-and-Play Approach for Adversarially Robust Generalization—0
A Latent Feature Analysis-based Approach for Spatio-Temporal Traffic Data Recovery—0
Semidefinite Programming versus Burer-Monteiro Factorization for Matrix Sensing—0
Adaptive and Implicit Regularization for Matrix CompletionCode1
Forecasting Algorithms for Causal Inference with Panel DataCode0
Propagation Map Reconstruction via Interpolation Assisted Matrix Completion—0
SP2: A Second Order Stochastic Polyak Method—0
A Perturbation Bound on the Subspace Estimator from Canonical ProjectionsCode0
Graph Neural Networks for Temperature-Dependent Activity Coefficient Prediction of Solutes in Ionic Liquids—0
Geometric Matrix Completion via Sylvester Multi-Graph Neural Network—0
MultiEarth 2022 -- The Champion Solution for the Matrix Completion Challenge via Multimodal Regression and Generation—0
Introducing the Huber mechanism for differentially private low-rank matrix completion—0
Robust Matrix Completion with Heavy-tailed Noise—0
A majorization-minimization algorithm for nonnegative binary matrix factorization—0
Quaternion Optimized Model with Sparse Regularization for Color Image Recovery—0
MultiEarth 2022 -- Multimodal Learning for Earth and Environment Workshop and Challenge—0
Survey of Matrix Completion Algorithms—0
Matrix Completion with Sparse Noisy Rows—0
Matrix Completion with Heterogonous Cost—0
Sensing Theorems for Unsupervised Learning in Linear Inverse ProblemsCode1
Perturbation Analysis of Randomized SVD and its Applications to Statistics—0
Bayesian Low-rank Matrix Completion with Dual-graph Embedding: Prior Analysis and Tuning-free Inference—0
Hierarchical Clustering and Matrix Completion for the Reconstruction of World Input-Output Tables—0
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