Abstract: In this study, we propose AlphaGrad, a novel adaptive loss blending strategy for optimizing multi-task learning (MTL) models in motor imagery (MI)-based electroencephalography (EEG) ...
Abstract: Federated Learning (FL) is an emerging computing paradigm to collaboratively train Machine Learning (ML) models across multi-source data while preserving privacy. The major challenge of ...
Abstract: Dynamic image degradations, including noise, blur and lighting inconsistencies, pose significant challenges in image restoration, often due to sensor limitations or adverse environmental ...
The ground is shifting: Inuit leader issues stark warning about Arctic sovereignty Assailant convicted after Barron Trump calls London police to report crime he saw on video Ontario government to fast ...
The core challenge in application of the ANN framework is selecting appropriate hyperparameters. The gradient descent algorithm is commonly used to optimize these hyperparameters by moving them in the ...
If you need support for a new econometric algorithm or have an idea for an implementation, please submit your request via GitHub Issues. After evaluation, we'll add it to our DEVPLAN for future ...
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