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   Articles with "hyperparameter" as a keyword



An automatic hyperparameter optimization DNN model for precipitation prediction

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recommendations! 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

Semi-supervised GAN with hybrid regularization and evolutionary hyperparameter tuning for accurate melanoma detection

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recommendations! Published in 2025 at "Scientific Reports"

DOI: 10.1038/s41598-025-17756-x

Abstract: Melanoma, influenced by changes in deoxyribonucleic acid (DNA), requires early detection for effective treatment. Traditional melanoma research often employs supervised learning methods, which necessitate large, labeled datasets and are sensitive to hyperparameter settings. This paper… read more here.

Keywords: detection; hyperparameter; hyperparameter tuning; semi supervised ... See more keywords

Automated, rapid, and convergent hyperparameter optimizer (ARCH) for neural network classifiers

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recommendations! Published in 2024 at "Quality Engineering"

DOI: 10.1080/08982112.2024.2374888

Abstract: Abstract There are many “hyperparameters” that dictate the performance of Artificial Neural Network (ANN) models in tasks such as classification and object detection. This study proposes an Automated, Rapid, Convergent Hyperparameter Optimizer (ARCH) implementing Design… read more here.

Keywords: hyperparameter; hyperparameter optimizer; convergent hyperparameter; automated rapid ... See more keywords

A geographic evolutionary framework with multi-task optimization of automatic hyperparameter tuning for spatially stratified machine learning models

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recommendations! Published in 2025 at "International Journal of Geographical Information Science"

DOI: 10.1080/13658816.2025.2502769

Abstract: Abstract The rapid growth of spatial data across various fields has made data-driven machine learning (ML) methods increasingly essential for spatial analysis. The performance of ML methods heavily depends on hyperparameter tuning (HPT), which becomes… read more here.

Keywords: hyperparameter; multi task; optimization; framework ... See more keywords

Optimizing the Hyperparameter Tuning of YOLOv5 for Underwater Detection

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recommendations! Published in 2022 at "IEEE Access"

DOI: 10.1109/access.2022.3174583

Abstract: This study optimized the latest YOLOv5 framework, including its subset models, with training on different datasets that differed in image contrast and cloudiness to assess model performances based on quantitative metrics and image processing speed.… read more here.

Keywords: optimizing hyperparameter; hyperparameter tuning; learning rate; hyperparameter ... See more keywords

Adaptive Similarity-Aware Hyperparameter Tuners for Classification Tasks

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recommendations! Published in 2023 at "IEEE Access"

DOI: 10.1109/access.2022.3229390

Abstract: With the success of deep learning in recent years, lots of different AI models have been applied to the real world. At the same time, how to train a model with good performance becomes a… read more here.

Keywords: similarity aware; hyperparameter; tuners classification; aware hyperparameter ... See more keywords
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Dynamical Hyperparameter Optimization via Deep Reinforcement Learning in Tracking

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recommendations! 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

A New Automatic Hyperparameter Recommendation Approach Under Low-Rank Tensor Completion e Framework

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recommendations! Published in 2022 at "IEEE Transactions on Pattern Analysis and Machine Intelligence"

DOI: 10.1109/tpami.2022.3195658

Abstract: Hyperparameter optimization (HPO), characterized by hyperparameter tuning, is not only a critical step for effective modeling but also is the most time-consuming process in machine learning. Traditional search-based algorithms tend to require extensive configuration evaluations… read more here.

Keywords: completion; hyperparameter; tensor completion; approach ... See more keywords

Hyperparameter-Free Localized Simple Multiple Kernel K-Means With Global Optimum.

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recommendations! Published in 2023 at "IEEE transactions on pattern analysis and machine intelligence"

DOI: 10.1109/tpami.2022.3233635

Abstract: The newly proposed localized simple multiple kernel k-means (SimpleMKKM) provides an elegant clustering framework which sufficiently considers the potential variation among samples. Although achieving superior clustering performance in some applications, we observe that it is… read more here.

Keywords: hyperparameter; free localized; multiple kernel; simple multiple ... See more keywords

Modeling of Hyperparameter Tuned Fuzzy Deep Neural Network–Based Human Activity Recognition for Disabled People

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recommendations! Published in 2024 at "Journal of Mathematics"

DOI: 10.1155/2024/5551009

Abstract: Human activity recognition (HAR) for disabled people is a vital research area, which aims to help individuals with disabilities in their daily lives. HAR involves using technology, typically wearable devices or sensors, to automatically identify… read more here.

Keywords: hyperparameter; human activity; har; activity recognition ... See more keywords

Multi-layer perceptron hyperparameter optimization using Jaya algorithm for disease classification

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recommendations! Published in 2024 at "Indonesian Journal of Electrical Engineering and Computer Science"

DOI: 10.11591/ijeecs.v35.i1.pp620-630

Abstract: This study introduces an innovative hyperparameter optimization approach for enhancing multilayer perceptrons (MLP) using the Jaya algorithm. Addressing the crucial role of hyperparameter tuning in MLP’s performance, the Jaya algorithm, inspired by social behavior, emerges… read more here.

Keywords: hyperparameter optimization; hyperparameter; using jaya; jaya algorithm ... See more keywords