Yingxiao Ye

Learning Risk Scores Robust to Unobserved Confounders

Categories Robust Optimization Tags , ,

We consider the problem of learning risk scores to prioritize individuals for scarce resources or interventions, from historical observational data affected by unobserved confounding. In settings such as public health and homelessness prevention, decisions about who receives a scarce resource (e.g., a hospital bed or housing) are often guided by a risk score assigned to … Read more

Robust Active Preference Elicitation

Categories Applications - OR and Management Sciences, Robust Optimization

We study the problem of strategically eliciting the preferences of a decision-maker through a moderate number of pairwise comparison queries with the goal of making them a high quality recommendation for a specific decision-making problem. We are particularly motivated by applications in high stakes domains, such as when choosing a policy for allocating scarce resources … Read more