Many applications involve estimation of parameters that generalize across multiple diverse, but related, data-scarce task environments. Bayesian active meta-learning, a form of …
In many settings, such as scientific inference, optimization, and transfer learning, the learner has a well-defined objective, which can be treated as estimation of a target parameter, and …
I Fraser, KG Balcombe - Certainty E⁄ Ects and Complexity Bias, 2023 - papers.ssrn.com
We introduce an alternative approach to experimental design aimed at collecting data for parametric estimation of the cumulative form of Prospect Theory (PT). Our approach …
e introduce an alternative approach to lottery prospects experimental design aimed at collecting experimental data for parametric estimation of the cumulative form of Prospect …
We study a setting in which an active meta-learner aims to separate the idiosyncracies of a particular task environment from information that will transfer between task environments. In …