Results 21 to 30 of about 492,500 (284)
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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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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A Randomized Sublinear Time Parallel GCD Algorithm for the EREW PRAM [PDF]
, 2010 We present a randomized parallel algorithm that computes the greatest common divisor of two integers of n bits in length with probability 1-o(1) that takes O(n loglog n / log n) expected time using n^{6+\epsilon} processors on the EREW PRAM parallel ...
Bach +22 more
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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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Randomized Speedup of the Bellman-Ford Algorithm [PDF]
, 2011 We describe a variant of the Bellman-Ford algorithm for single-source shortest paths in graphs with negative edges but no negative cycles that randomly permutes the vertices and uses this randomized order to process the vertices within each pass of the ...
Bannister, Michael J., Eppstein, David
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New Bounds for Randomized List Update in the Paid Exchange Model [PDF]
, 2020 We study the fundamental list update problem in the paid exchange model P^d. This cost model was introduced by Manasse, McGeoch and Sleator [M.S. Manasse et al., 1988] and Reingold, Westbrook and Sleator [N. Reingold et al., 1994]. Here the given list of
Albers, Susanne, Janke, Maximilian
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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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