Abstract: With its robust capabilities for non-linear regression and classification, kernel-based learning has emerged as a fundamental component of state-of-the-art machine learning approaches. In ...

Traditional cloud architectures are buckling under the weight of generative AI. To move from pilots to production, ...

Overview: AI skills in 2026 require both technical understanding and the ability to apply them responsibly at work.Machine ...

Researchers at National University of Singapore used multiple interpretable machine learning methods to predict traffic congestion in in Alameda ...

Abstract: The application of Machine Learning for predictive analysis in healthcare, particularly for diseases like diabetes, has proven highly beneficial. This study introduces an optimized Light ...

Demographics, language, social media activity, and temporal features should be considered to maximize the accuracy of depression prediction models. Additionally, the effects of social media platform ...