Search alternatives:
required optimization » guided optimization (Expand Search), resource optimization (Expand Search), feature optimization (Expand Search)
based optimization » whale optimization (Expand Search)
data required » data acquired (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
based based » based case (Expand Search), based basis (Expand Search), ranked based (Expand Search)
required optimization » guided optimization (Expand Search), resource optimization (Expand Search), feature optimization (Expand Search)
based optimization » whale optimization (Expand Search)
data required » data acquired (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
based based » based case (Expand Search), based basis (Expand Search), ranked based (Expand Search)
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Proposed Algorithm.
Published 2025“…EHRL integrates Reinforcement Learning (RL) with Deep Neural Networks (DNNs) to dynamically optimize binary offloading decisions, which in turn obviates the requirement for manually labeled training data and thus avoids the need for solving complex optimization problems repeatedly. …”
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Comparisons between ADAM and NADAM optimizers.
Published 2025“…EHRL integrates Reinforcement Learning (RL) with Deep Neural Networks (DNNs) to dynamically optimize binary offloading decisions, which in turn obviates the requirement for manually labeled training data and thus avoids the need for solving complex optimization problems repeatedly. …”
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Medium-scale dataset comparative analysis using the number of features selected.
Published 2023Subjects: -
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Large-scale dataset comparative analysis using the number of features selected.
Published 2023Subjects: -
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