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Low-Rank Matrix Completion

6 papers with code ยท Methodology
Subtask of Matrix Completion

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Latest papers without code

The Sparse Reverse of Principal Component Analysis for Fast Low-Rank Matrix Completion

4 Oct 2019

The proposed approach maintains smoothness across the matrix, produces accurate estimates of the missing data, converges iteratively, and it is computationally tractable with a controllable upper bound on the number of iterations until convergence.

IMAGE RECONSTRUCTION LOW-RANK MATRIX COMPLETION MULTI-TASK LEARNING RECOMMENDATION SYSTEMS TIME SERIES

Low-rank matrix completion and denoising under Poisson noise

11 Jul 2019

This paper considers the problem of estimating a low-rank matrix from the observation of all, or a subset, of its entries in the presence of Poisson noise.

DENOISING LOW-RANK MATRIX COMPLETION

A divide-and-conquer algorithm for binary matrix completion

9 Jul 2019

We propose an algorithm for low rank matrix completion for matrices with binary entries which obtains explicit binary factors.

LOW-RANK MATRIX COMPLETION RECOMMENDATION SYSTEMS

Depth Restoration: A fast low-rank matrix completion via dual-graph regularization

5 Jul 2019

As a real scenes sensing approach, depth information obtains the widespread applications.

LOW-RANK MATRIX COMPLETION

Efficiently escaping saddle points on manifolds

10 Jun 2019

Specifically, for an arbitrary Riemannian manifold $\mathcal{M}$ of dimension $d$, a sufficiently smooth (possibly non-convex) objective function $f$, and under weak conditions on the retraction chosen to move on the manifold, with high probability, our version of PRGD produces a point with gradient smaller than $\epsilon$ and Hessian within $\sqrt{\epsilon}$ of being positive semidefinite in $O((\log{d})^4 / \epsilon^{2})$ gradient queries.

LOW-RANK MATRIX COMPLETION

Guaranteed Matrix Completion Under Multiple Linear Transformations

CVPR 2019

Low-rank matrix completion (LRMC) is a classical model in both computer vision (CV) and machine learning, and has been successfully applied to various real applications.

IMAGE INPAINTING LOW-RANK MATRIX COMPLETION

Adaptive Matrix Completion for the Users and the Items in Tail

22 Apr 2019

In this work, we show that the skewed distribution of ratings in the user-item rating matrix of real-world datasets affects the accuracy of matrix-completion-based approaches.

COLLABORATIVE FILTERING LOW-RANK MATRIX COMPLETION

Noisy Matrix Completion: Understanding Statistical Guarantees for Convex Relaxation via Nonconvex Optimization

20 Feb 2019

This paper studies noisy low-rank matrix completion: given partial and noisy entries of a large low-rank matrix, the goal is to estimate the underlying matrix faithfully and efficiently.

LOW-RANK MATRIX COMPLETION

Double Weighted Truncated Nuclear Norm Regularization for Low-Rank Matrix Completion

7 Jan 2019

The truncated nuclear norm regularization (TNNR) method is applicable in real-world scenarios.

LOW-RANK MATRIX COMPLETION

Communication Efficient Parallel Algorithms for Optimization on Manifolds

NeurIPS 2018

Our work aims to fill a critical gap in the literature by generalizing parallel inference algorithms to optimization on manifolds.

LOW-RANK MATRIX COMPLETION