Regularization in Deep Learning is very important to overcome overfitting. When your training accuracy is very high, but test ...

What is overfitting and underfitting in machine learning? What is Bias and Variance? Overfitting and Underfitting are two common problems in machine learning and Deep learning. If a model has low ...

Ruyi Ding (Northeastern University), Tong Zhou (Northeastern University), Lili Su (Northeastern University), Aidong Adam Ding (Northeastern University), Xiaolin Xu (Northeastern University), Yunsi Fei ...

ESG indices in emerging markets often lack long, transparent historical records, making them difficult to analyze with ...

By transferring temporal knowledge from complex time-series models to a compact model through knowledge distillation and attention mechanisms, the ...

According to TII’s technical report, the hybrid approach allows Falcon H1R 7B to maintain high throughput even as response ...

Duke University engineers are using artificial intelligence to do something scientists have chased for centuries; turn messy, ...

A practical guide to the four strategies of agentic adaptation, from "plug-and-play" components to full model retraining.

Explainable AI plays a central role in validating model behavior. Using established explainability techniques, the study examines which financial variables drive fraud predictions. The results show a ...

WiMi Hologram Cloud Inc. ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, launched a hybrid quantum neural network structure (H-QNN) for image ...

anthropomorphism: When humans tend to give nonhuman objects humanlike characteristics. In AI, this can include believing a ...