Search Results - "randomized algorithm"

Finding Structure with Randomness: Probabilistic Algorithms for Constructing Approximate Matrix Decompositions by Halko, N., Martinsson, P. G., Tropp, J. A.

“…Low-rank matrix approximations, such as the truncated singular value decomposition and the rank-revealing QR decomposition, play a central role in data…”
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Randomized nonnegative matrix factorization by Erichson, N. Benjamin, Mendible, Ariana, Wihlborn, Sophie, Kutz, J. Nathan

“…•A novel randomized hierarchical alternating least squares algorithm for NMF.•The randomized algorithm scales up to big data.•The algorithm outperforms…”
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Parallel PCA–KPCA for nonlinear process monitoring by Jiang, Qingchao, Yan, Xuefeng

“…Both linear and nonlinear relationships may exist among process variables, and monitoring a process with such complex relationships among variables is…”
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Practical Sketching Algorithms for Low-Rank Matrix Approximation by Tropp, Joel A., Yurtsever, Alp, Udell, Madeleine, Cevher, Volkan

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Fast and Accurate Randomized Algorithms for Linear Systems and Eigenvalue Problems by Nakatsukasa, Yuji, Tropp, Joel A.

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A randomized algorithm based approach to fault detection for uncertain systems subject to deception attack by Zhao, Zhen, Liu, Peter Xiaoping, Gao, Jinfeng

“…This paper presents a fault detection strategy for discrete uncertain systems subject to deception attack based on the probabilistic framework. Probabilistic…”
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A randomized-algorithm-based decomposition-ensemble learning methodology for energy price forecasting by Tang, Ling, Wu, Yao, Yu, Lean

“…Inspired by the interesting idea of randomization, some powerful but time-consuming decomposition-ensemble learning paradigms can be extended into extremely…”
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Randomized Nyström Preconditioning by Frangella, Zachary, Tropp, Joel A., Udell, Madeleine

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The Optimal Noise-Adding Mechanism in Differential Privacy by Quan Geng, Viswanath, Pramod

“…Differential privacy is a framework to quantify to what extent individual privacy in a statistical database is preserved while releasing useful aggregate…”
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Generative modeling via tensor train sketching by Hur, YoonHaeng, Hoskins, Jeremy G., Lindsey, Michael, Stoudenmire, E.M., Khoo, Yuehaw

“…In this paper, we introduce a sketching algorithm for constructing a tensor train representation of a probability density from its samples. Our method deviates…”
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Tikhonov regularization with MTRSVD method for solving large-scale discrete ill-posed problems by Huang, Guangxin, Liu, Yuanyuan, Yin, Feng

“…Regularization is possibly the most popular method for solving discrete ill-posed problems, whose solution is less sensitive to the error in the observed…”
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Non-negative Tucker decomposition with graph regularization and smooth constraint for clustering by Liu, Qilong, Lu, Linzhang, Chen, Zhen

“…Non-negative Tucker decomposition (NTD) and its graph regularized extensions are the most popular techniques for representing high-dimensional non-negative…”
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Improved stochastic configuration networks with vision patch fusion method for industrial image classification by Li, Ruilin, Jiao, Wenhua, Zhu, Yongjun

“…This paper contributes to the advancement of stochastic configuration neural networks (SCN) in the field of visual applications. The proposed image…”
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A hybrid dynamic mode decomposition algorithm combining random and sparsity promoting and its application to viscoelastic flow around circular cylinder by Li, Xuan, Su, Jin, Feng, Jin-Qian, Lei, Xiong, Zhang, Rui-Bo

“…•We propose a hybrid method called sparsity promoting randomized dynamic mode decomposition (SP-RDMD).•SP-RDMD can reconstruct the overall flow pattern of the…”
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Low-rank approximation: Randomized QR with Column Pivoting and related methods using sparse projection and pass-efficient techniques by Ji, Ying, Feng, Yuehua, Dong, Yongxin, Guan, Jinrui, Han, Xiao

“…Currently, several efficient algorithms utilize randomization techniques to compute low-rank matrix approximations, such as Randomized QR with Column Pivoting…”
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Randomized progressive iterative approximation for B-spline curve and surface fittings by Wu, Nian-Ci, Liu, Cheng-Zhi

“…For large-scale data fitting, the least-squares progressive iterative approximation is a widely used method in many applied domains because of its intuitive…”
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Fast and Forward Stable Randomized Algorithms for Linear Least-Squares Problems by Epperly, Ethan N.

“…Not provided…”
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Randomized quaternion tensor UTV decompositions for color image and color video processing by Yang, Liqiao, Miao, Jifei, Jiang, Tai-Xiang, Zhang, Yanlin, Kou, Kit Ian

“…In this paper, we propose novel quaternion matrix UTV (QUTV) and quaternion tensor UTV (QTUTV) decomposition methods, specifically designed for color image and…”
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Solving the system of nonsingular tensor equations via randomized Kaczmarz-like method by Wang, Xuezhong, Che, Maolin, Mo, Changxin, Wei, Yimin

“…A great deal of attention has been paid to solve the system of tensor equations in recent years for its applications in various fields. In this paper, the…”
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A Butterfly-Based Direct Integral-Equation Solver Using Hierarchical LU Factorization for Analyzing Scattering From Electrically Large Conducting Objects by Han Guo, Yang Liu, Jun Hu, Michielssen, Eric

“…A butterfly-based direct combined-field integral-equation (CFIE) solver for analyzing scattering from electrically large, perfect electrically conducting…”
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