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 ...

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

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

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

A research team has introduced a lightweight artificial intelligence method that accurately identifies wheat growth stages ...

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

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 ...

Bipolar Disorder, Digital Phenotyping, Multimodal Learning, Face/Voice/Phone, Mood Classification, Relapse Prediction, T-SNE, Ablation Share and Cite: de Filippis, R. and Al Foysal, A. (2025) ...

Explore how AI-driven anomaly detection enhances the security of Model Context Protocol (MCP) deployments, protecting AI infrastructure from evolving threats with real-time insights.