Results 11 to 20 of about 435,592 (297)
Structured Gradient Descent for Fast Robust Low-Rank Hankel Matrix Completion [PDF]
SIAM Journal on Scientific Computing, 2022 We study the robust matrix completion problem for the low-rank Hankel matrix, which detects the sparse corruptions caused by extreme outliers while we try to recover the original Hankel matrix from the partial observation.
Hanqin Cai, Jian-Feng Cai, Juntao You
semanticscholar +1 more source
Nonconvex Tensor Relative Total Variation for Image Completion
Mathematics, 2023 Image completion, which falls to a special type of inverse problems, is an important but challenging task. The difficulties lie in that (i) the datasets usually appear to be multi-dimensional; (ii) the unavailable or corrupted data entries are randomly ...
Yunqing Bai, Jihong Pei, Min Li
doaj +1 more source
A Singular Value Thresholding Algorithm for Matrix Completion [PDF]
SIAM Journal on Optimization, 2008 This paper introduces a novel algorithm to approximate the matrix with minimum nuclear norm among all matrices obeying a set of convex constraints. This problem may be understood as the convex relaxation of a rank minimization problem and arises in many ...
Jian-Feng Cai, E. Candès, Zuowei Shen
semanticscholar +1 more source
Rank-Adaptive Tensor Completion Based on Tucker Decomposition
Entropy, 2023 Tensor completion is a fundamental tool to estimate unknown information from observed data, which is widely used in many areas, including image and video recovery, traffic data completion and the multi-input multi-output problems in information theory ...
Siqi Liu, Xiaoyu Shi, Qifeng Liao
doaj +1 more source
Rail transit OD‐matrix completion via manifold regularized tensor factorisation
IET Intelligent Transport Systems, 2021 Urban rail transit has become an indispensable mode in major cities worldwide regarding the advantages of large capacity, high speed, punctuality, and environmental protection.
Hanxuan Dong +5 more
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Simple, fast, and flexible framework for matrix completion with infinite width neural networks [PDF]
Proceedings of the National Academy of Sciences of the United States of America, 2021 Significance Matrix completion is a fundamental problem in machine learning that arises in various applications. We envision that our infinite width neural network framework for matrix completion will be easily deployable and produce strong baselines for
Adityanarayanan Radhakrishnan +3 more
semanticscholar +1 more source
Deterministic Polynomial Time Algorithms for Matrix Completion Problems [PDF]
SIAM journal on computing (Print), 2009 We present new deterministic algorithms for several cases of the maximum rank matrix completion problem (for short matrix completion), i.e., the problem of assigning values to the variables in a given symbolic matrix to maximize the resulting matrix rank.
G. Ivanyos +2 more
semanticscholar +1 more source
The CP-Matrix Completion Problem [PDF]
SIAM Journal on Matrix Analysis and Applications, 2014 arXiv admin note: text overlap with arXiv:1210.6930 by other ...
Zhou, Anwa, Fan, Jinyan
openaire +2 more sources
Mobile group intelligence aware network log information collection based on Markov prediction
Xi'an Gongcheng Daxue xuebao, 2022 Aiming at the problems of low completion rate and large remaining proportion of collection tasks in traditional information collection methods, the Markov prediction model of multi sensing location is used to dynamically collect the real-time information
CAI Bo
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Bayesian Uncertainty Quantification for Low-Rank Matrix Completion [PDF]
Bayesian Analysis, 2021 We consider the problem of uncertainty quantification for an unknown low-rank matrix $\mathbf{X}$, given a partial and noisy observation of its entries.
H. Yuchi, Simon Mak, Yao Xie
semanticscholar +1 more source