68 citations · 126 across the 7 of their papers we have counts for
12 papers
Faking feature importance: A cautionary tale on the use of differentially-private synthetic data
Oscar Giles, Kasra Hosseini, Grigorios Mingas +13
Synthetic datasets are often presented as a silver-bullet solution to the problem of privacy-preserving data publishing. However, for many applications, synthetic data has been sho…
An Empirical Comparison of Bias Reduction Methods on Real-World Problems in High-Stakes Policy Settings
Hemank Lamba, Kit T. Rodolfa, Rayid Ghani
Applications of machine learning (ML) to high-stakes policy settings -- such as education, criminal justice, healthcare, and social service delivery -- have grown rapidly in recent…
Empirical observation of negligible fairness-accuracy trade-offs in machine learning for public policy
Kit T. Rodolfa, Hemank Lamba, Rayid Ghani
Growing use of machine learning in policy and social impact settings have raised concerns for fairness implications, especially for racial minorities. These concerns have generated…
A Recommendation and Risk Classification System for Connecting Rough Sleepers to Essential Outreach Services
Harrison Wilde, Lucia Lushi Chen, Austin Nguyen +7
Rough sleeping is a chronic problem faced by some of the most disadvantaged people in modern society. This paper describes work carried out in partnership with Homeless Link, a UK-…
A Machine Learning System for Retaining Patients in HIV Care
Avishek Kumar, Arthi Ramachandran, Adolfo De Unanue +7
Retaining persons living with HIV (PLWH) in medical care is paramount to preventing new transmissions of the virus and allowing PLWH to live normal and healthy lifespans. Maintaini…
Case Study: Predictive Fairness to Reduce Misdemeanor Recidivism Through Social Service Interventions
Kit T. Rodolfa, Erika Salomon, Lauren Haynes +3
The criminal justice system is currently ill-equipped to improve outcomes of individuals who cycle in and out of the system with a series of misdemeanor offenses. Often due to cons…