arXiv · 2608.28179
Conformal Risk-Averse Decision Making with Optimized Certainty Equivalent Risk Control
Abstract
We study risk-averse decision making, in which an agent selects actions while being uncertain about the true system state. The risk is measured via optimized certainty equivalent (OCE) metrics, which generalize popular criteria such as mean-variance risk and conditional value-at-risk (CVaR). We characterize the optimal policy under known distributions, and show that it reduces to a prediction set-based solution for the CVaR. This provides an operational interpretation of conformal prediction-type prediction sets. For unknown distributions, we develop a data-driven calibration strategy, based on a synthetic model for the likelihood and held-out calibration data, yielding high-probability control of the OCE risk. The approach is evaluated on two wireless beamforming settings.
Explore related subjects
Keep this discovery
Amirmohammad Farzaneh, Osvaldo Simeone. 2026-08-28. Conformal Risk-Averse Decision Making with Optimized Certainty Equivalent Risk Control. https://arxiv.org/abs/2608.28179
Cite the original work for its findings. Save a collection to share your selection of sources.
Discover connections
Connections use source metadata and explicit phrase matches, not verified experimental comparisons.