Designing Fair, Efficient, and Interpretable Policies for Prioritizing Homeless Youth for Housing Resources
By Javad Azizi, Phebe Vayanos, Bryan Wilder, Eric Rice, Milind Tambe. 2018
65 citations recorded by the source corpus.
Subfields: Building and Construction, Electrical and Electronic Engineering, Management Science and Operations Research
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Management Science and Operations Research
Citations in the corpus
- Learning Optimal and Fair Decision Trees for Non-Discriminative Decision-Making (2019, methodology): “The classes of decision trees above were originally proposed in (Azizi et al. 2018) in the context of policy design for resource allocation problems.”
- Learning Optimal Classification Trees: Strong Max-Flow Formulations (2020, background): “(c) We present the first polyhedral results concerning the convex hull of the feasible region of decision trees: we show that all cuts added in our proposed Benders method are facets of this decision tree polytope. (d) We conduct extensive computational studies, showing that our formulations improve”
- Interpretable Optimal Stopping (2018, background): “With regard to dynamic problems, Bertsimas et al. (2013) considers the problem of designing a dynamic allocation policy for allocating deceased donor kidneys to patients requiring a kidney transplant that maximizes efficiency while respecting certain fairness constraints.”