. Successful application of active learning requires an effective metric in order to gauge the informativeness of data. Current …Given the computational challenges associated with valuing large variable annuity (VA) portfolios, a variety of data … mining frameworks, including metamodeling and active learning, have been proposed in recent years. Active learning, a …

This paper addresses the steep learning curve in Machine Learning faced by noncomputer scientists, particularly social … adage "once you understand OLS, you can work your way up to any other estimator," and apply it to Machine Learning. Focusing … and fire some trailblazers to the forefront of AI and causal machine learning. …

data streams. Numerous machine learning-based models are developed to detect the concept drift in machine learning … devises dynamic streaming data analytics depending on the optimized hybrid deep learning classifier and Optimized Key …The generation of huge data with high velocity creates alteration in the distribution of the stream data, which is …

The literature on adaptive learning suggests that it can provide significant improvements to the educational process … and numerous studies have found a necessity for personalised learning, which is one of the strong suits of adaptive … learning. Adaptive learning platforms require that content be effective, and lack thereof has hindered large-scale adoption by …