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Nikolaos Bakas
Function approximation is a fundamental process in a variety of problems in computational mechanics, structural engineering, as well as other domains that require the precise approximation of a phenomenon with an analytic function. This work demonstrates...
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Lidong Liu, Shidang Li, Mingsheng Wei, Jinsong Xu and Bencheng Yu
Network energy resources are limited in communication systems, which may cause energy shortages in mobile devices at the user end. Active Reconfigurable Intelligent Surfaces (A-RIS) not only have phase modulation properties but also enhance the signal st...
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Alexander Robitzsch
Item response theory (IRT) models are frequently used to analyze multivariate categorical data from questionnaires or cognitive test data. In order to reduce the model complexity in item response models, regularized estimation is now widely applied, addi...
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Andrea D?Ambrosio and Roberto Furfaro
This paper demonstrates the utilization of Pontryagin Neural Networks (PoNNs) to acquire control strategies for achieving fuel-optimal trajectories. PoNNs, a subtype of Physics-Informed Neural Networks (PINNs), are tailored for solving optimal control pr...
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Vedat Dogan and Steven Prestwich
In a multi-objective optimization problem, a decision maker has more than one objective to optimize. In a bilevel optimization problem, there are the following two decision-makers in a hierarchy: a leader who makes the first decision and a follower who r...
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Thomas Parr, Karl Friston and Peter Zeidman
Bayesian inference typically focuses upon two issues. The first is estimating the parameters of some model from data, and the second is quantifying the evidence for alternative hypotheses?formulated as alternative models. This paper focuses upon a third ...
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Tushar Ganguli and Edwin K. P. Chong
We present a novel technique for pruning called activation-based pruning to effectively prune fully connected feedforward neural networks for multi-object classification. Our technique is based on the number of times each neuron is activated during model...
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Muhammad Sheraz, Teong Chee Chuah, Mardeni Bin Roslee, Manzoor Ahmed, Amjad Iqbal and Ala?a Al-Habashna
Data caching is a promising technique to alleviate the data traffic burden from the backhaul and minimize data access delay. However, the cache capacity constraint poses a significant challenge to obtaining content through the cache resource that degrade...
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Daniel S. Soper
When designed correctly, radial basis function (RBF) neural networks can approximate mathematical functions to any arbitrary degree of precision. Multilayer perceptron (MLP) neural networks are also universal function approximators, but RBF neural networ...
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Nikolay Nefedov, Bogdan Tishchenko and Natalia Levashova
An algorithm is presented for the construction of an asymptotic approximation of a stable stationary solution to a diffusion equation system in a two-dimensional domain with a smooth boundary and a source function that is discontinuous along some smooth ...
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