Results 11 to 20 of about 295,614 (312)
Stochastic Generalized Method of Moments [PDF]
Journal of Computational and Graphical Statistics, 2011 The generalized method of moments (GMM) is a very popular estimation and inference procedure based on moment conditions. When likelihood-based methods are difficult to implement, one can often derive various moment conditions and construct the GMM objective function.
Yin, Guosheng +3 more
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A Hybrid Stochastic Deterministic Algorithm for Solving Unconstrained Optimization Problems
Mathematics, 2022 In this paper, a new deterministic method is proposed. This method depends on presenting (suggesting) some modifications to existing parameters of some conjugate gradient methods.
Ahmad M. Alshamrani +4 more
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Training Artificial Neural Networks Using a Global Optimization Method That Utilizes Neural Networks
AI, 2023 Perhaps one of the best-known machine learning models is the artificial neural network, where a number of parameters must be adjusted to learn a wide range of practical problems from areas such as physics, chemistry, medicine, etc.
Ioannis G. Tsoulos, Alexandros Tzallas
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NeuralMinimizer: A Novel Method for Global Optimization
Information, 2023 The problem of finding the global minimum of multidimensional functions is often applied to a wide range of problems. An innovative method of finding the global minimum of multidimensional functions is presented here.
Ioannis G. Tsoulos +3 more
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Efficient simulation of stochastic chemical kinetics with the Stochastic Bulirsch-Stoer extrapolation method [PDF]
, 2014 BackgroundBiochemical systems with relatively low numbers of components must be simulated stochastically in order to capture their inherent noise. Although there has recently been considerable work on discrete stochastic solvers, there is still a need ...
Barrio Solórzano, Manuel +11 more
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Multi-element stochastic reduced basis methods [PDF]
, 2007 This paper presents mutli-element Stochastic Reduced Basis Methods (ME-SRBMs) for solving linear stochastic partial differential equations. In ME-SRBMs, the domain of definition of the random inputs is decomposed into smaller subdomains or random ...
Surya Mohan, P. +5 more
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Proceedings, 2018 The design of energy-efficient electric motor is a complex problem since diverse requirements and competing goals have to be fulfilled simultaneously. Therefore, different approaches to the design optimization of electric motors have been developed, each
Johannes Schmelcher +4 more
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Proceedings, 2018 Designing energy-efficient electric motor is a task where multiple goals have to be achieved at once. To find the best design possible, different approaches have been developed.
Johannes Schmelcher +4 more
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On a Stochastic Approximation Method [PDF]
The Annals of Mathematical Statistics, 1954 Asymptotic properties are established for the Robbins-Monro [1] procedure of stochastically solving the equation $M(x) = \alpha$. Two disjoint cases are treated in detail. The first may be called the "bounded" case, in which the assumptions we make are similar to those in the second case of Robbins and Monro. The second may be called the "quasi-linear"
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Química Nova, 2008 The paper presents an introductory and general discussion on the quantum Monte Carlo methods, some fundamental algorithms, concepts and applicability. In order to introduce the quantum Monte Carlo method, preliminary concepts associated with Monte Carlo ...
Wagner Fernando Delfino Angelotti +3 more
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