Results 21 to 30 of about 212,881 (293)
Hyperparameter-Optimization-Inspired Long Short-Term Memory Network for Air Quality Grade Prediction
Information, 2023 In the world, with the continuous development of modern society and the acceleration of urbanization, the problem of air pollution is becoming increasingly salient. Methods for predicting the air quality grade and determining the necessary governance are
Dushi Wen +5 more
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Algorithms, 2023 Heart disease is a significant global health issue, contributing to high morbidity and mortality rates. Early and accurate heart disease prediction is crucial for effectively preventing and managing the condition. However, this remains a challenging task
Daniyal Asif +3 more
semanticscholar +1 more source
Depthwise Hyperparameter Transfer in Residual Networks: Dynamics and Scaling Limit [PDF]
International Conference on Learning Representations, 2023 The cost of hyperparameter tuning in deep learning has been rising with model sizes, prompting practitioners to find new tuning methods using a proxy of smaller networks.
Blake Bordelon +4 more
semanticscholar +1 more source
No More Pesky Hyperparameters: Offline Hyperparameter Tuning for RL
, 2022 The performance of reinforcement learning (RL) agents is sensitive to the choice of hyperparameters. In real-world settings like robotics or industrial control systems, however, testing different hyperparameter configurations directly on the environment can be financially prohibitive, dangerous, or time consuming.
Wang, Han +9 more
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Сучасні інформаційні системи, 2019 This paper contains formal problem definition of predicting unfavorable airborne events during flight. Restrictions and assumptions are put into the prognosis method of unfavorable airborne events during flight.
Evhenii Gryshmanov +2 more
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Applied Sciences, 2022 Hyperparameter tuning is a critical function necessary for the effective deployment of most machine learning (ML) algorithms. It is used to find the optimal hyperparameter settings of an ML algorithm in order to improve its overall output performance. To
Ismail Damilola Raji +5 more
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Hyperparameter-free losses for model-based monocular reconstruction [PDF]
, 2019 This work proposes novel hyperparameter-free losses for single view 3D reconstruction with morphable models (3DMM). We dispense with the hyperparameters used in other works by exploiting geometry, so that the shape of the object and the camera pose are ...
Batard, Thomas +3 more
core +2 more sources
Sensors, 2021 Electrical resistivity is used to obtain various types of information for soil strata. Hence, the prediction of electrical resistivity is helpful to predict the future behavior of soil.
Seung-Jae Lee, Hyung-Koo Yoon
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Hyperparameter Optimization for 1D-CNN-Based Network Intrusion Detection Using GA and PSO
Mathematics, 2023 This study presents a comprehensive exploration of the hyperparameter optimization in one-dimensional (1D) convolutional neural networks (CNNs) for network intrusion detection.
Dusmurod Kilichev, Wooseong Kim
semanticscholar +1 more source
Future Internet, 2020 Web service composition is the process of combining and reusing existing web services to create new business processes to satisfy specific user requirements. Reliability plays an important role in ensuring the quality of web service composition. However,
Yang Song, Yawen Wang, Dahai Jin
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