Abstract: With its inherent causal reasoning and superior capacity for handling uncertainty, the belief rule base (BRB) has been widely applied in complex systems modeling. As a generalization of ...
A simulation study is designed to explore the accuracy of attribute parameter estimation in the crossed random effects linear logistic test model (CRELLTM) with the impact of Q-matrix misspecification ...
We present a machine learning method based on random projections with Johnson-Lindenstrauss (JL) and/or Rahimi and Recht (2007) Random Fourier Features (RFFN) for efficiently learning linear and ...
Abstract: This article presents a novel variable-parameter variable-activation-function finite-time neural network (VPA-FTNN) to deal with joint-angle drift issues of redundant-robotic arms. Different ...
Many types of economic problems require that we consider two variables at the same time. A typical example is the relation between price of a commodity and the demand or supply of that commodity. The ...
In recent years, neural networks have once again triggered an increased interest among researchers in the machine learning community. So-called deep neural networks model functions using a composition ...
When you have a density function, but you would like to create a set of sample points from that density function, you can use linear interpolate sampling. Using the evaluation of the density at the ...
ABSTRACT: This paper presents a new dimension reduction strategy for medium and large-scale linear programming problems. The proposed method uses a subset of the original constraints and combines two ...
Quantum annealing (QA) can be competitive to classical algorithms in optimizing continuous-variable functions when running on appropriate hardware, show researchers from Tokyo Tech. By comparing the ...
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