15 citations · 59 across the 17 of their papers we have counts for
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cs.AI2023★ 6 cited
Reflections from the Workshop on AI-Assisted Decision Making for Conservation
Lily Xu, Esther Rolf, Sara Beery +21
In this white paper, we synthesize key points made during presentations and discussions from the AI-Assisted Decision Making for Conservation workshop, hosted by the Center for Res…
cs.LG2023★ 1 cited
Leaving the Nest: Going Beyond Local Loss Functions for Predict-Then-Optimize
Sanket Shah, Andrew Perrault, Bryan Wilder +1
Predict-then-Optimize is a framework for using machine learning to perform decision-making under uncertainty. The central research question it asks is, "How can the structure of a…