4 accepted papers
As AI systems’ sophistication and proliferation have increased, awareness of the risks has grown proportionally. The AI industry is increasingly emphasizing the need for transparency, with proposals ranging from standardizing use of technical disclosures, like model cards, to regulatory licensing re…
In many applied fields, researchers are ofteninterested in tailoring treatments to unit-levelcharacteristics in order to optimize an outcomeof interest. Methods for identifying andestimating treatment policies are the subjectof the dynamic treatment regime literature. Separately, in many settings th…
A foundational tool for making causal inferences is the emulation of randomized control trials via variable interventions. This approach has been applied to a wide variety of contexts, from health to economics [3, 6]. Variable interventions have long been studied in independent and identically distr…
The assumption that data samples are independent and identically distributed (iid) is standard in many areas of statistics and machine learning. Nevertheless, in some settings, such as social networks, infectious disease modeling, and reasoning with spatial and temporal data, this assumption is fals…