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Published in 2021 at "Applied Intelligence"
DOI: 10.1007/s10489-021-02507-y
Abstract: Deep neural networks (DNN) have gained remarkable success on many rainfall predictions tasks in recent years. However, the performance of DNN highly relies upon the hyperparameter setting. In order to design DNNs with the best…
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Keywords:
dnn;
precipitation;
hyperparameter optimization;
hyperparameter ... See more keywords
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Published in 2017 at "Machine Learning"
DOI: 10.1007/s10994-017-5684-y
Abstract: Algorithm selection as well as hyperparameter optimization are tedious task that have to be dealt with when applying machine learning to real-world problems. Sequential model-based optimization (SMBO), based on so-called “surrogate models”, has been employed…
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Keywords:
surrogate;
model;
optimization;
transfer ... See more keywords
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Published in 2022 at "IEEE Systems Journal"
DOI: 10.1109/jsyst.2021.3130080
Abstract: Electrical load forecasting is one of the critical tasks that helps power utility companies in planning and operation as well as the energy managementsystem (EMS) in controlling and optimizing the power grid’s performance. It guarantees…
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Keywords:
learning algorithms;
hyperparameter optimization;
load forecasting;
parallel distributed ... See more keywords
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Published in 2021 at "IEEE Transactions on Pattern Analysis and Machine Intelligence"
DOI: 10.1109/tpami.2019.2956703
Abstract: Hyperparameters are numerical pre-sets whose values are assigned prior to the commencement of a learning process. Selecting appropriate hyperparameters is often critical for achieving satisfactory performance in many vision problems, such as deep learning-based visual…
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Keywords:
optimization via;
hyperparameter optimization;
dynamical hyperparameter;
hyperparameter ... See more keywords
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Published in 2022 at "Computational Intelligence and Neuroscience"
DOI: 10.1155/2022/7097044
Abstract: The unprecedented Corona Virus Disease (COVID-19) pandemic has put the world in peril and shifted global landscape in unanticipated ways. The SARSCoV2 virus, which caused the COVID-19 outbreak, first appeared in Wuhan, Hubei Province, China,…
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Keywords:
neural network;
stock market;
hyperparameter optimization;
volatility ... See more keywords
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Published in 2022 at "Journal of Healthcare Engineering"
DOI: 10.1155/2022/9882288
Abstract: Heart disease is a severe disorder, which inflicts an adverse burden on all societies and leads to prolonged suffering and disability. We developed a risk evaluation model based on visible low-cost significant noninvasive attributes using…
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Keywords:
hyperparameter optimization;
optimization machine;
risk;
heart disease ... See more keywords
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Published in 2020 at "Frontiers in Neuroscience"
DOI: 10.3389/fnins.2020.00667
Abstract: In resource-constrained environments, such as low-power edge devices and smart sensors, deploying a fast, compact, and accurate intelligent system with minimum energy is indispensable. Embedding intelligence can be achieved using neural networks on neuromorphic hardware.…
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Keywords:
network;
accurate;
multi objective;
hardware ... See more keywords
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Published in 2022 at "Algorithms"
DOI: 10.3390/a16010017
Abstract: Training and evaluating the performance of many competing Artificial Intelligence (AI)/Machine Learning (ML) models can be very time-consuming and expensive. Furthermore, the costs associated with this hyperparameter optimization task grow exponentially when cross validation is…
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Keywords:
cross validation;
successive halving;
halving;
hyperparameter optimization ... See more keywords
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Published in 2023 at "Sensors"
DOI: 10.3390/s23115058
Abstract: With the rapid development of sensor technology, structural health monitoring data have tended to become more massive. Deep learning has advantages when handling big data, and has therefore been widely researched for diagnosing structural anomalies.…
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Keywords:
hyperparameter optimization;
bayesian based;
hyperparameter;
optimization cnn ... See more keywords