10 citations · 18 across the 9 of their papers we have counts for
5 papers · 1 filter
Productionized Fairness Measurement Under Privacy Constraints
Osonde A. Osoba, Yuzi He, Saikrishna Badrinarayanan +3
Fairness measurements in the form of disaggregated evaluations often rely on demographic signals that are legally constrained or culturally sensitive. Race and ethnicity signals ar…
Privacy-Preserving Race/Ethnicity Estimation for Algorithmic Bias Measurement in the U.S
Saikrishna Badrinarayanan, Osonde Osoba, Miao Cheng +4
AI fairness measurements, including tests for equal treatment, often take the form of disaggregated evaluations of AI systems. Such measurements are an important part of Responsibl…
Deep Generative Modeling in Network Science with Applications to Public Policy Research
Gavin S. Hartnett, Raffaele Vardavas, Lawrence Baker +5
Network data is increasingly being used in quantitative, data-driven public policy research. These are typically very rich datasets that contain complex correlations and inter-depe…
A Generative Machine Learning Approach to Policy Optimization in Pursuit-Evasion Games
Shiva Navabi, Osonde A. Osoba
We consider a pursuit-evasion game [11] played between two agents, 'Blue' (the pursuer) and 'Red' (the evader), over time steps. Red aims to attack Blue's territory. Blue's obj…
Policy-focused Agent-based Modeling using RL Behavioral Models
Osonde A. Osoba, Raffaele Vardavas, Justin Grana +2
Agent-based Models (ABMs) are valuable tools for policy analysis. ABMs help analysts explore the emergent consequences of policy interventions in multi-agent decision-making settin…