Model averaging has long been proposed as a powerful alternative to model selection in regression analysis. However, how well it performs in high-dimensional regression is still poorly understood.

Partial linear models have been widely used as flexible method for modelling linear components in conjunction with non-parametric ones. Despite the presence of the non-parametric part, the linear, ...

Researchers have explained how large language models like GPT-3 are able to learn new tasks without updating their parameters, despite not being trained to perform those tasks. They found that these ...

In the modern field of deep learning, linear attention mechanisms are gradually becoming a powerful tool for handling long sequence data. Recent research has revealed how these mechanisms 'decay' ...

Microbiome sequencing data are known to be biased; the measured taxa relative abundances can be systematically distorted from their true values at every step in the experimental/analysis workflow. If ...

Citations: Blattberg, Robert. 1981. An Assessment of the Contribution of Log Linear Models to Marketing Research. Journal of Marketing. (2)89-97.

Modeling a railroad is hard. Railroads are large, linear pieces of civil engineering. So many modelers are drawn to the smallest scale they can use. Recently a new scale, named T, at 1:450 has been ...