2 citations · 3 across the 4 of their papers we have counts for
3 papers · 1 filter
Learning Who to Treat When Treatment is Missing
Johnna Sundberg, Rayid Ghani, Eli Ben-Michael +1
Policy learning methods are increasingly used to inform treatment allocation under budget constraints. Most proposed methods assume complete treatment data, yet applications freque…
Breaking the Cycle of Incarceration With Targeted Mental Health Outreach: A Case Study in Machine Learning for Public Policy
Kit T. Rodolfa, Erika Salomon, Jin Yao +9
Many incarcerated individuals face significant and complex challenges, including mental illness, substance dependence, and homelessness, yet jails and prisons are often poorly equi…
Aequitas Flow: Streamlining Fair ML Experimentation
Sérgio Jesus, Pedro Saleiro, Inês Oliveira e Silva +5
Aequitas Flow is an open-source framework and toolkit for end-to-end Fair Machine Learning (ML) experimentation, and benchmarking in Python. This package fills integration gaps tha…