Results 11 to 20 of about 182,395 (164)
Energy-Based Adaptive CUR Matrix Decomposition
IEEE Access, 2023 CUR decompositions are interpretable data analysis tools that express a data matrix in terms of a small number of actual columns and/or actual rows of the data matrix.
Liwen Xu, Xuejiao Zhao, Yongxia Zhang
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IEEE Access, 2018 Determining the variable transmission structure is the key step in designing a distributed monitoring scheme for multiunit processes. This paper proposes randomized algorithm (RA) integrated with evolutionary optimization-based data-driven distributed ...
Qingchao Jiang, Yang Wang, Xuefeng Yan
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Scholarpedia, 2007 We consider algorithmic randomness in the Cantor space C of the infinite binary sequences. By an algorithmic randomness concept one specifies a set of elements of C, each of which is assigned the property of being random. Miscellaneous notions from computability theory are used in the definitions of randomness concepts that are essentially rooted in ...
Jan Reimann, Rodney Downey
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Randomized Matrix Decompositions Using R
Journal of Statistical Software, 2019 Matrix decompositions are fundamental tools in the area of applied mathematics, statistical computing, and machine learning. In particular, low-rank matrix decompositions are vital, and widely used for data analysis, dimensionality reduction, and data ...
N. Benjamin Erichson +3 more
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Randomized Average Kaczmarz Algorithm for Tensor Linear Systems
Mathematics, 2022 For solving tensor linear systems under the tensor–tensor t-product, we propose the randomized average Kaczmarz (TRAK) algorithm, the randomized average Kaczmarz algorithm with random sampling (TRAKS), and their Fourier version, which can be effectively ...
Wendi Bao +4 more
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Sublinear Time Motif Discovery from Multiple Sequences
Algorithms, 2013 In this paper, a natural probabilistic model for motif discovery has been used to experimentally test the quality of motif discovery programs. In this model, there are k background sequences, and each character in a background sequence is a random ...
Yunhui Fu, Bin Fu, Yuan Xue
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Probabilistic Algorithmic Knowledge [PDF]
Logical Methods in Computer Science, 2005 The framework of algorithmic knowledge assumes that agents use deterministic knowledge algorithms to compute the facts they explicitly know. We extend the framework to allow for randomized knowledge algorithms.
Joseph Y. Halpern, Riccardo Pucella
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Journal of King Saud University: Computer and Information Sciences, 2021 Highlights: • A novel chaotic asymmetric-key color image encryption algorithm is proposed. • The multiplicative coupled Chebyshev-based encryption scheme allows arbitrary sizes of keyspace.
Ali Shakiba
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Massive Fishing Website URL Parallel Filtering Method
IEEE Access, 2018 A randomized fingerprint model is proposed, which can effectively reduce the false positive rate by generating a unique fingerprint for each URL. The model is also used to improve the Wu and Manber (WM) algorithm, which is a multi-string matching ...
Dongliang Xu +5 more
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Efficient Asynchronous Semi-Stochastic Block Coordinate Descent Methods for Large-Scale SVD
IEEE Access, 2021 Eigenvector computation such as Singular Value Decomposition (SVD) is one of the most fundamental problems in machine learning, optimization and numerical linear algebra.
Fanhua Shang +4 more
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