Capturing and Interpreting Unique Information

Author name not available (Why is that?)

Publication date: 23 February 2023

Abstract: Partial information decompositions (PIDs), which quantify information interactions between three or more variables in terms of uniqueness, redundancy and synergy, are gaining traction in many application domains. However, our understanding of the operational interpretations of PIDs is still incomplete for many popular PID definitions. In this paper, we discuss the operational interpretations of unique information through the lens of two well-known PID definitions. We reexamine an interpretation from statistical decision theory showing how unique information upper bounds the risk in a decision problem. We then explore a new connection between the two PIDs, which allows us to develop an informal but appealing interpretation, and generalize the PID definitions using a common Lagrangian formulation. Finally, we provide a new PID definition that is able to capture the information that is unique. We also show that it has a straightforward interpretation and examine its properties.

This page was built for publication: Capturing and Interpreting Unique Information

Report a bug (only for logged in users!)Click here to report a bug for this page (MaRDI item Q6427378)