Results 41 to 50 of about 3,678,430 (211)
Self-Supervised Feature Specific Neural Matrix Completion
IEEE Access, 2020 Unsupervised matrix completion algorithms mostly model the data generation process by using linear latent variable models. Recently proposed algorithms introduce non-linearity via multi-layer perceptrons (MLP), and self-supervision by setting separate ...
Mehmet Aktukmak +2 more
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A Nonconvex Method to Low-Rank Matrix Completion
IEEE Access, 2022 In recent years, the problem of recovering a low-rank matrix from partial entries, known as low-rank matrix completion problem, has attracted much attention in many applications.
Haizhen He +3 more
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Matrix Completion With Data-Dependent Missingness Probabilities [PDF]
IEEE Transactions on Information Theory, 2021 The problem of completing a large matrix with lots of missing entries has received widespread attention in the last couple of decades. Two popular approaches to the matrix completion problem are based on singular value thresholding and nuclear norm ...
Sohom Bhattacharya, S. Chatterjee
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Robust Global Motion Estimation with Matrix Completion [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2014 In this paper we address the problem of estimating the attitudes and positions of a set of cameras in an external coordinate system. Starting from a conventional global structure-from-motion pipeline, we present some substantial advances.
F. Arrigoni +4 more
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Local low-rank approach to nonlinear matrix completion
EURASIP Journal on Advances in Signal Processing, 2021 This paper deals with a problem of matrix completion in which each column vector of the matrix belongs to a low-dimensional differentiable manifold (LDDM), with the target matrix being high or full rank.
Ryohei Sasaki +3 more
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Deep Sparse Depth Completion Using Multi-Affinity Matrix
IEEE Access, 2023 Image-guided depth completion aims to generate dense depth maps from sparse depth maps guided by their corresponding color (RGB) images. In this paper, we propose deep sparse depth completion using multi-affinity matrix.
Wei Zhao, Cheolkon Jung, Jaekwang Kim
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Empirical Bayes matrix completion [PDF]
Computational Statistics & Data Analysis, 2019 We develop an empirical Bayes (EB) algorithm for the matrix completion problems. The EB algorithm is motivated from the singular value shrinkage estimator for matrix means by Efron and Morris (1972). Since the EB algorithm is essentially the EM algorithm applied to a simple model, it does not require heuristic parameter tuning other than tolerance ...
Takeru Matsuda, Fumiyasu Komaki
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Dynamic Matrix Completion Based State Estimation in Distribution Grids
IEEE Transactions on Industrial Informatics, 2022 The power distribution network is undergoing tremendous transformation due to an increase in the penetration of renewable energy resources and electric vehicles.
Biswajeet Rout +2 more
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Matrix completion theorems [PDF]
Proceedings of the American Mathematical Society, 1985 The author studies matrices over a principal ideal ring R and obtains a number of results on completing, or embedding, such matrices so that the resulting matrices satisfy certain given conditions. For example, if a row of length \(n\geq 3\) has no common divisors in R, then it is the first row of a multiplicative commutator in \(M_ n(R)\) of two ...
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Weighted truncated nuclear norm regularization for low-rank quaternion matrix completion [PDF]
Journal of Visual Communication and Image Representation, 2021 In recent years, quaternion matrix completion (QMC) based on low-rank regularization has been gradually used in image de-noising and de-blurring.Unlike low-rank matrix completion (LRMC) which handles RGB images by recovering each color channel separately,
Liqiao Yang, K. Kou, Jifei Miao
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