Analysis of bootstrap and subsampling in high-dimensional regularized regression
We investigate popular resampling methods for estimating the uncertainty of statistical
models, such as subsampling, bootstrap and the jackknife, and their performance in high …
models, such as subsampling, bootstrap and the jackknife, and their performance in high …
Deal, or no deal (or who knows)? Forecasting Uncertainty in Conversations using Large Language Models
Effective interlocutors account for the uncertain goals, beliefs, and emotions of others. But
even the best human conversationalist cannot perfectly anticipate the trajectory of a …
even the best human conversationalist cannot perfectly anticipate the trajectory of a …
[PDF][PDF] Post-Doctorate position: Sequential set-valued learning and application to citizen sciences
Objectives Several previous works focus on building for a given X either a smallest set-
valued classifier with 1− α coverage for small α∈(0, 1), or the set-valued with the highest …
valued classifier with 1− α coverage for small α∈(0, 1), or the set-valued with the highest …