Results 31 to 40 of about 522,371 (218)
Simple Synchronous and Asynchronous Algorithms for Distributed Minimax Optimization
SICE Journal of Control, Measurement, and System Integration, 2017 Synchronous and asynchronous algorithms are presented for distributed minimax optimization. The objective here is to realize the minimization of the maximum of component functions over the standard multi-agent network, where each node of the network ...
Kenta Hanada +3 more
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Approximation method for a fractional order transfer function with zero and pole
Archives of Control Sciences, 2014 The paper presents an approximation method for elementary fractional order transfer function containing both pole and zero. This class of transfer functions can be applied for example to build model - based special control algorithms. The proposed method
Oprzędkiewicz Krzysztof
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Optimal Centers’ Allocation in Smoothing or Interpolating with Radial Basis Functions
Mathematics, 2021 Function interpolation and approximation are classical problems of vital importance in many science/engineering areas and communities. In this paper, we propose a powerful methodology for the optimal placement of centers, when approximating or ...
Pedro González-Rodelas +3 more
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Dual Taylor Series, Spline Based Function and Integral Approximation and Applications
Mathematical and Computational Applications, 2019 In this paper, function approximation is utilized to establish functional series approximations to integrals. The starting point is the definition of a dual Taylor series, which is a natural extension of a Taylor series, and spline based series ...
Roy M. Howard
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Optimal algorithms for doubly weighted approximation of univariate functions
Journal of Approximation Theory, 2016 For given positive integer \( r , 1 \leq p \leq \infty\), and a positive and measurable weight function \(\psi : \mathbb{R}_+ \rightarrow \mathbb{R}_+ \), the authors consider the space \(F=F(r,p,\psi)\) consisting of functions \(f: \mathbb{R}_+ \rightarrow \mathbb{R} \), with (locally) absolutely continuous derivative \(f^{(r-1)}\), and \( \parallel f^
Kuo, F. Y. +2 more
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Approximate Implicitization Using Linear Algebra
Journal of Applied Mathematics, 2012 We consider a family of algorithms for approximate implicitization of rational parametric curves and surfaces. The main approximation tool in all of the approaches is the singular value decomposition, and they are therefore well suited to floating-point ...
Oliver J. D. Barrowclough, Tor Dokken
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IEEE Access, 2018 Reinforcement learning (RL) is an important machine learning paradigm that can be used for learning from the data obtained by the human-computer interface and the interaction in human-centered smart systems. One of the essential problems in RL algorithms
Dazi Li +3 more
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A sample decreasing threshold greedy-based algorithm for big data summarisation
Journal of Big Data, 2021 As the scale of datasets used for big data applications expands rapidly, there have been increased efforts to develop faster algorithms. This paper addresses big data summarisation problems using the submodular maximisation approach and proposes an ...
Teng Li +2 more
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Machines, 2021 In this paper, we consider the problem of selecting the most efficient optimization algorithm for neural network approximation—solving optimal control problems with mixed constraints.
Irina Bolodurina, Lyubov Zabrodina
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Approximation Algorithms for Stochastic Boolean Function Evaluation and Stochastic Submodular Set Cover [PDF]
, 2013 Stochastic Boolean Function Evaluation is the problem of determining the value of a given Boolean function f on an unknown input x, when each bit of x_i of x can only be determined by paying an associated cost c_i.
Deshpande, Amol +2 more
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