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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 251–300 of 796 papers

TitleStatusHype
WARPd: A linearly convergent first-order method for inverse problems with approximate sharpness conditionsCode0
Uncertainty Quantification For Low-Rank Matrix Completion With Heterogeneous and Sub-Exponential Noise—0
Projection-Free Algorithm for Stochastic Bi-level Optimization—0
Reconstruction of Fragmented Trajectories of Collective Motion using Hadamard Deep Autoencoders—0
Computational Graph Completion—0
Factorization Approach for Low-complexity Matrix Completion Problems: Exponential Number of Spurious Solutions and Failure of Gradient Methods—0
One-Bit Matrix Completion with Differential Privacy—0
Multi-way Clustering and Discordance Analysis through Deep Collective Matrix Tri-Factorization—0
Provable Low Rank Plus Sparse Matrix Separation Via Nonconvex Regularizers—0
Weighted Low Rank Matrix Approximation and Acceleration—0
Accelerated Stochastic Gradient for Nonnegative Tensor Completion and Parallel Implementation—0
On the Fundamental Limits of Matrix Completion: Leveraging Hierarchical Similarity Graphs—0
Matrix Completion of World Trade—0
Provable Tensor-Train Format Tensor Completion by Riemannian Optimization—0
Attribute-based Explanations of Non-Linear Embeddings of High-Dimensional Data—0
Private Alternating Least Squares: Practical Private Matrix Completion with Tighter Rates—0
Causal Inference with Corrupted Data: Measurement Error, Missing Values, Discretization, and Differential Privacy—0
Low Rank Quaternion Matrix Recovery via Logarithmic Approximation—0
Global Convergence of Gradient Descent for Asymmetric Low-Rank Matrix Factorization—0
GNMR: A provable one-line algorithm for low rank matrix recoveryCode0
Matrix Completion with Model-free Weighting—0
A Pre-training Oracle for Predicting Distances in Social Networks—0
Patch Tracking-based Streaming Tensor Ring Completion for Visual Data Recovery—0
Low-Rank Hankel Tensor Completion for Traffic Speed EstimationCode0
Multi-source Learning via Completion of Block-wise Overlapping Noisy Matrices—0
Sharp Restricted Isometry Property Bounds for Low-rank Matrix Recovery Problems with Corrupted Measurements—0
Deep learned SVT: Unrolling singular value thresholding to obtain better MSE—0
On the Optimality of Nuclear-norm-based Matrix Completion for Problems with Smooth Non-linear Structure—0
Nonparametric Trace Regression in High Dimensions via Sign Series Representation—0
Implicit Regularization in Deep Tensor Factorization—0
Matrix completion based on Gaussian parameterized belief propagation—0
Multi-target prediction for dummies using two-branch neural networks—0
PAC-Bayesian Matrix Completion with a Spectral Scaled Student Prior—0
NoisyCUR: An algorithm for two-cost budgeted matrix completionCode0
Joint Matrix Completion and Compressed Sensing for State Estimation in Low-observable Distribution System—0
Adversarially-Trained Nonnegative Matrix FactorizationCode0
Simulation comparisons between Bayesian and de-biased estimators in low-rank matrix completionCode0
A Neural Network for SemigroupsCode0
Structure-Preserving Progressive Low-rank Image Completion for Defending Adversarial Attacks—0
Progresses and Challenges in Link Prediction—0
Implicit Regularization in Tensor FactorizationCode0
Forecasting Nonnegative Time Series via Sliding Mask Method (SMM) and Latent Clustered Forecast (LCF)—0
Policy Augmentation: An Exploration Strategy for Faster Convergence of Deep Reinforcement Learning AlgorithmsCode0
Wasserstein Graph Neural Networks for Graphs with Missing Attributes—0
Matrix Decomposition on Graphs: A Functional View—0
Exact Linear Convergence Rate Analysis for Low-Rank Symmetric Matrix Completion via Gradient Descent—0
Riemannian Perspective on Matrix Factorization—0
Unlabeled Principal Component Analysis and Matrix CompletionCode0
Sparse Array Beamformer Design for Active and Passive Sensing—0
Local Search Algorithms for Rank-Constrained Convex Optimization—0
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