Results 11 to 20 of about 190,858 (265)
A Randomized Distributed Kaczmarz Algorithm and Anomaly Detection
The Kaczmarz algorithm is an iterative method for solving systems of linear equations. We introduce a randomized Kaczmarz algorithm for solving systems of linear equations in a distributed environment, i.e., the equations within the system are ...
Fritz Keinert, Eric S. Weber
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Sublinear Time Motif Discovery from Multiple Sequences
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 Parameterized Algorithms for the Kidney Exchange Problem
In order to increase the potential kidney transplants between patients and their incompatible donors, kidney exchange programs have been created in many countries.
Mugang Lin +3 more
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Energy-Based Adaptive CUR Matrix Decomposition
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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Probabilistic Algorithmic Randomness
AbstractWe introduce martingales defined by probabilistic strategies, in which randomness is used to decide whether to bet. We show that different criteria for the success of computable probabilistic strategies can be used to characterize ML-randomness, computable randomness, and partial computable randomness.
Sam Buss, Mia Minnes
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Randomized Average Kaczmarz Algorithm for Tensor Linear Systems
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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Randomized priority algorithms
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Angelopoulos, Spyros, Borodin, Allan
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Proofs of randomized algorithms in Coq [PDF]
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Audebaud, Philippe +1 more
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COARSE REDUCIBILITY AND ALGORITHMIC RANDOMNESS [PDF]
AbstractA coarse description of a set A ⊆ ω is a set D ⊆ ω such that the symmetric difference of A and D has asymptotic density 0. We study the extent to which noncomputable information can be effectively recovered from all coarse descriptions of a given set A, especially when A is effectively random in some sense.
Denis R. Hirschfeldt +3 more
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Algorithmic Randomness and Fourier Analysis [PDF]
Suppose $1 < p < \infty$. Carleson's Theorem states that the Fourier series of any function in $L^p[-π, π]$ converges almost everywhere. We show that the Schnorr random points are precisely those that satisfy this theorem for every $f \in L^p[-π, π]$ given natural computability conditions on $f$ and $p$.
Johanna N. Y. Franklin +2 more
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