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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 576–600 of 796 papers

TitleStatusHype
Ocean Reverberation Suppression via Matrix Completion with Sensor Failure—0
On adaptivity and minimax optimality of two-sided nearest neighbors—0
On Asymptotic Linear Convergence of Projected Gradient Descent for Constrained Least Squares—0
On Deterministic Sampling Patterns for Robust Low-Rank Matrix Completion—0
One-Bit Matrix Completion with Differential Privacy—0
One-sided Matrix Completion from Two Observations Per Row—0
Online Algorithms for Factorization-Based Structure from Motion—0
Online high rank matrix completion—0
Online Low Rank Matrix Completion—0
Online Matrix Completion: A Collaborative Approach with Hott Items—0
Online Matrix Completion and Online Robust PCA—0
Online Matrix Completion Through Nuclear Norm Regularisation—0
Online Matrix Completion with Side Information—0
Online Optimization for Large-Scale Max-Norm Regularization—0
Online Optimization for Max-Norm Regularization—0
Online Policy Learning and Inference by Matrix Completion—0
Online Variational Bayesian Subspace Filtering with Applications—0
On Tensor Completion via Nuclear Norm Minimization—0
On the Convergence of Stochastic Gradient Descent with Low-Rank Projections for Convex Low-Rank Matrix Problems—0
On the convex geometry of blind deconvolution and matrix completion—0
On the Fundamental Limits of Matrix Completion: Leveraging Hierarchical Similarity Graphs—0
On the Optimality of Nuclear-norm-based Matrix Completion for Problems with Smooth Non-linear Structure—0
Can Learning Be Explained By Local Optimality In Robust Low-rank Matrix Recovery?—0
On the Power of Adaptivity in Matrix Completion and Approximation—0
On the Power of Truncated SVD for General High-rank Matrix Estimation Problems—0
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