Presenting a clear, presentable plan to clients starts with understanding the context and framework of their goal. Giving clients useful information that is relevant to their plan may still not ...
Achieving high reliability in AI systems—such as autonomous vehicles that stay on course even in snowstorms or medical AI ...
There has been a 47% reduction in contraception-related contacts with Sexual and Reproductive Health (SRH) services in the ...
Machine learning holds great promise for classifying and identifying fossils, and has recently been marshaled to identify trackmakers of dinosaur ...
Time series classification is widely used in many fields, but it often suffers from a lack of labeled data. To address this, researchers commonly apply data augmentation techniques that generate ...
In a Nature Communications study, researchers from China have developed an error-aware probabilistic update (EaPU) method ...
LLM-Based Data Augmentation Method in Reinforcement Learning With Machine-Unlearning and Fine-Tuning
Abstract: Data augmentation in reinforcement learning (RL) aims to generate diverse and extensive datasets to enhance the learning process. Most existing studies on RL augmentation employ sample-based ...
1 Qingdao Huanghai University, Qingdao, China 2 College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao, China High-resolution remote sensing imagery is a powerful ...
Abstract: Supervised human activity recognition (HAR) with sensor data typically demands substantial labeled datasets to train robust models. Contrastive learning offers a self-supervised alternative ...
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