An automatic hyperparameter optimization DNN model for precipitation prediction
Sign Up to like & getrecommendations! 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… read more here.
Keywords: dnn; precipitation; hyperparameter optimization; hyperparameter ... See more keywords
Scalable Gaussian process-based transfer surrogates for hyperparameter optimization
Sign Up to like & getrecommendations! 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… read more here.
Keywords: surrogate; model; optimization; transfer ... See more keywords
Deep Learning Algorithms and Parallel Distributed Computing Techniques for High-Resolution Load Forecasting Applying Hyperparameter Optimization
Sign Up to like & getrecommendations! 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… read more here.
Keywords: learning algorithms; hyperparameter optimization; load forecasting; parallel distributed ... See more keywords
Dynamical Hyperparameter Optimization via Deep Reinforcement Learning in Tracking
Sign Up to like & getrecommendations! 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… read more here.
Keywords: optimization via; hyperparameter optimization; dynamical hyperparameter; hyperparameter ... See more keywords
Impact of Healthcare on Stock Market Volatility and Its Predictive Solution Using Improved Neural Network
Sign Up to like & getrecommendations! 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,… read more here.
Keywords: neural network; stock market; hyperparameter optimization; volatility ... See more keywords
An Intelligent and Reliable Hyperparameter Optimization Machine Learning Model for Early Heart Disease Assessment Using Imperative Risk Attributes
Sign Up to like & getrecommendations! 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… read more here.
Keywords: hyperparameter optimization; optimization machine; risk; heart disease ... See more keywords
Bayesian Multi-objective Hyperparameter Optimization for Accurate, Fast, and Efficient Neural Network Accelerator Design
Sign Up to like & getrecommendations! 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.… read more here.
Keywords: network; accurate; multi objective; hardware ... See more keywords
Hyperparameter Optimization Using Successive Halving with Greedy Cross Validation
Sign Up to like & getrecommendations! 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… read more here.
Keywords: cross validation; successive halving; halving; hyperparameter optimization ... See more keywords
Bayesian-Based Hyperparameter Optimization of 1D-CNN for Structural Anomaly Detection
Sign Up to like & getrecommendations! 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.… read more here.
Keywords: hyperparameter optimization; bayesian based; hyperparameter; optimization cnn ... See more keywords