Abstract: Data stream learning is an emerging machine learning paradigm designed for environments where data arrive continuously and must be processed in real time. Unlike traditional batch learning, ...

Data Science Program, University of Delaware, Newark, Delaware 19716, United States Department of Materials Science and Engineering, University of Delaware, Newark, Delaware 19716, United States ...

Background: There is a growing enthusiasm for machine learning (ML) among academics and health care practitioners. Despite the transformative potential of ML-based applications for patient care, their ...

The Society for Financial Econometrics (SoFiE) Summer School is an annual week-long research-based course for PhD students, new faculty, and professionals in financial econometrics. For the first two ...

Caption:MIT researchers created a periodic table of machine learning that shows how more than 20 classical algorithms are connected. The new framework sheds light on how scientists could fuse ...

Linux has long been the backbone of modern computing, serving as the foundation for servers, cloud infrastructures, embedded systems, and supercomputers. As artificial intelligence (AI) and machine ...

Abstract: This paper presents a dynamic selector model for data workload prediction. A main function responsible for selecting the most accurate Machine Learning Algorithm (e.g., Linear Regression, ...

In the past few years, HR has seen a significant transformation driven by the rise of machine learning tools and technology. 1 These tools extract insights, patterns, and predict trends from massive ...

1 Espace Dev, Université de Perpignan Via Domitia, Perpignan, France 2 UMR Espace Dev (228), Université Montpellier, IRD, Montpellier, France Endurance-trained athletes require physiological ...