According to Andrej Karpathy (@karpathy), maintaining strong regularization is crucial to prevent model degradation when applying Reinforcement Learning from Human Feedback (RLHF) in AI systems ...

Linear mixed model-based approaches have emerged as a more efficient methodology for the analysis of MET data. Recently, these mixed model approaches have become predominant, as they provide a ...

ABSTRACT. Utilizing selection indices is an effective strategy for the simultaneous evaluation of multiple traits in kale breeding programs. This approach allows for the selection of kale genotypes ...

In this investigation, linear models used for quality prediction of a final product are compared and evaluated using data from a real manufacturing process in forming technology (i.e., flexible ...

Abstract: Assumptions play a pivotal role in the selection and efficacy of statistical models, as unmet assumptions can lead to flawed conclusions and impact decision-making. In both traditional ...

At the risk of making the module on linear models too long, I still have the feeling that the "Regularization in linear model" section could have an exercise on regression and/or a notebook on ...

The Champions League proper returns next month and this season it will have a brand new format. The ‘Swiss Model’ makes its debut and, as a result, the Champions League draw tomorrow (Thursday) is ...

The paper introduces the PILOT learning algorithm for constructing linear model trees, enhancing decision tree interpretability and performance. It uses a standard regression model with centered ...