Results 91 to 100 of about 3,678,430 (211)
A New Algorithm for Positive Semidefinite Matrix Completion
Journal of Applied Mathematics, 2016 Positive semidefinite matrix completion (PSDMC) aims to recover positive semidefinite and low-rank matrices from a subset of entries of a matrix. It is widely applicable in many fields, such as statistic analysis and system control.
Fangfang Xu, Peng Pan
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Exponential Family Matrix Completion under Structural Constraints [PDF]
, 2015 We consider the matrix completion problem of recovering a structured matrix from noisy and partial measurements. Recent works have proposed tractable estimators with strong statistical guarantees for the case where the underlying matrix is low--rank, and
Ghosh, Joydeep +2 more
core
Background Subtraction via Fast Robust Matrix Completion
, 2017 Background subtraction is the primary task of the majority of video inspection systems. The most important part of the background subtraction which is common among different algorithms is background modeling.
Ostadabbas, Sarah, Rezaei, Behnaz
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Leveraged Matrix Completion With Noise
IEEE Transactions on CyberneticsThis manuscript has been accepted for publication as a regular paper in the IEEE Transactions on ...
Xinjian Huang +3 more
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RW-MC:self-adaptive random walk based matrix completion algorithm
Tongxin xuebao, 2017 Concerning the continually perceiving performance of virtual access points (VAP) was urgent in software-defined wireless network (SDWN),with the features of VAPs’ measurement data (VMD),a self-adaptive matrix completion algorithm based on random walk was
Xin-heng WANG +4 more
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, 2017 We propose a novel algorithm for sequential matrix completion in a recommender system setting, where the $(i,j)$th entry of the matrix corresponds to a user $i$'s rating of product $j$. The objective of the algorithm is to provide a sequential policy for user-product pair recommendation which will yield the highest possible ratings after a finite time ...
Marsden, Annie, Bacallado, Sergio
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iMTF-GRN: Integrative Matrix Tri-Factorization for Inference of Gene Regulatory Networks
IEEE Access, 2019 Gene Regulatory Network (GRN) inference using computational approaches has been a highly pursued problem in bioinformatics. Various approaches have been developed to infer GRNs from gene expression data including statistical, machine learning and ...
Nisar Wani, Khalid Raza
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IEEE Access, 2020 Assessment of lower limb motion function is crucial for clinicians to treat patients effectively. However, diagnosis accuracy is still affected by clinical experience.
Yan Zhang +4 more
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Matrix Completion With Covariate Information
Journal of the American Statistical Association, 2018 This paper investigates the problem of matrix completion from corrupted data, when additional covariates are available. Despite being seldomly considered in the matrix completion literature, these covariates often provide valuable information for completing the unobserved entries of the high-dimensional target matrix A0. Given a covariate matrix X with
Xiaojun Mao +2 more
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Approximation theory and matrix completions
Linear Algebra and its Applications, 2004 The authors start by proving some interesting results in low-dimensional matrix approximation problems. For example, they show that (1) a one-dimensional subspace \({\mathcal L}\) of \(M_n(\mathbb{C})\), the space of \(n\)-by-\(n\) complex matrices, is Chebyshev (that is, every matrix in \(M_n(\mathbb{C})\) has a unique approximant in \({\mathcal L}\))
Hadwin, D, Larson, D.R, Timotin, D
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