Abstract: Data augmentation is an effective way to overcome the overfitting problem of deep learning models. However, most existing studies on data augmentation work on framelike data (e.g., images), ...
Abstract: Federated Learning (FL) is a collaborative machine learning (ML) framework that combines on-device training and server-based aggregation to train a common ML model among distributed agents.
The emergence of tools like ChatGPT complicates the ability of instructors to assess genuine learning, raising concerns about the future of this educational model. The COVID pandemic accelerated the ...
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