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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 401–450 of 796 papers

TitleStatusHype
High-dimensional Time Series Prediction with Missing Values—0
High-Rank Matrix Completion and Clustering under Self-Expressive Models—0
Identifying global optimality for dictionary learning—0
Identifying Influential Entries in a Matrix—0
IHT-Inspired Neural Network for Single-Snapshot DOA Estimation with Sparse Linear Arrays—0
Image Tag Completion and Refinement by Subspace Clustering and Matrix Completion—0
Implicit bias of SGD in L_2-regularized linear DNNs: One-way jumps from high to low rank—0
Implicit Regularization in Deep Tensor Factorization—0
Implicit Regularization in Nonconvex Statistical Estimation: Gradient Descent Converges Linearly for Phase Retrieval, Matrix Completion, and Blind Deconvolution—0
Implicit Regularization in Nonconvex Statistical Estimation: Gradient Descent Converges Linearly for Phase Retrieval and Matrix Completion—0
Imposing Consistency Properties on Blackbox Systems with Applications to SVD-Based Recommender Systems—0
Improved Approximation Algorithms for Low-Rank Problems Using Semidefinite Optimization—0
Improving Matrix Completion by Exploiting Rating Ordinality in Graph Neural Networks—0
Improving Temporal Interpolation of Head and Body Pose using Gaussian Process Regression in a Matrix Completion Setting—0
InceptionGCN: Receptive Field Aware Graph Convolutional Network for Disease Prediction—0
Incoherence-Optimal Matrix Completion—0
Individualized Rank Aggregation using Nuclear Norm Regularization—0
Inductive Collaborative Filtering via Relation Graph Learning—0
Inductive Matrix Completion and Root-MUSIC-Based Channel Estimation for Intelligent Reflecting Surface (IRS)-Aided Hybrid MIMO Systems—0
Inductive Pairwise Ranking: Going Beyond the n log(n) Barrier—0
Inference and Uncertainty Quantification for Noisy Matrix Completion—0
Influenza Modeling Based on Massive Feature Engineering and International Flow Deconvolution—0
Information-theoretic Bounds on Matrix Completion under Union of Subspaces Model—0
Intelligent Reflecting Surface for Massive Device Connectivity: Joint Activity Detection and Channel Estimation—0
Interpretable Matrix Completion: A Discrete Optimization Approach—0
Introducing the Huber mechanism for differentially private low-rank matrix completion—0
Iterative missing value imputation based on feature importance—0
Joint Matrix Completion and Compressed Sensing for State Estimation in Low-observable Distribution System—0
k-Space Deep Learning for Reference-free EPI Ghost Correction—0
L_2,1-Norm Regularized Quaternion Matrix Completion Using Sparse Representation and Quaternion QR Decomposition—0
Large-Scale Low-Rank Matrix Learning with Nonconvex Regularizers—0
Large-Scale Matrix Factorization with Missing Data under Additional Constraints—0
Large-Scale Sparse Inverse Covariance Estimation via Thresholding and Max-Det Matrix Completion—0
Latent Variable Models for Predicting File Dependencies in Large-Scale Software Development—0
Learning Counterfactual Distributions via Kernel Nearest Neighbors—0
Learning from Ambiguously Labeled Face Images—0
Learning Iterative Reasoning through Energy Diffusion—0
Learning Latent Features with Pairwise Penalties in Low-Rank Matrix Completion—0
Learning Mixtures of Discrete Product Distributions using Spectral Decompositions—0
Learning of Generalized Low-Rank Models: A Greedy Approach—0
Learning Parameters for Weighted Matrix Completion via Empirical Estimation—0
Learning Transition Operators From Sparse Space-Time Samples—0
Learning Translations via Matrix Completion—0
Leave-One-Out Analysis for Nonconvex Robust Matrix Completion with General Thresholding Functions—0
Lifelong Matrix Completion with Sparsity-Number—0
Link Discovery using Graph Feature Tracking—0
Link Prediction via Matrix Completion—0
Local Search Algorithms for Rank-Constrained Convex Optimization—0
Log-Normal Matrix Completion for Large Scale Link Prediction—0
Low Permutation-rank Matrices: Structural Properties and Noisy Completion—0
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