11 papers
Online Learning with Multiple Fairness Regularizers via Graph-Structured Feedback
Quan Zhou, Jakub Marecek, Robert Shorten
There is an increasing need to enforce multiple, often competing, measures of fairness within automated decision systems. The appropriate weighting of these fairness objectives is…
Tractable Probabilistic Models for Investment Planning
Nicolas M. Cuadrado A., Mohannad Takrouri, JiÅÃ NÄmeÄek +2
Investment planning in power utilities, such as generation and transmission expansion, requires decisions under substantial uncertainty over decade--long horizons for policies, dem…
Intersectional Fairness via Mixed-Integer Optimization
JiÅÃ NÄmeÄek, Mark Kozdoba, Illia Kryvoviaz +2
The deployment of Artificial Intelligence in high-risk domains, such as finance and healthcare, necessitates models that are both fair and transparent. While regulatory frameworks,…
Stochastic Sample Approximations of (Local) Moduli of Continuity
Rodion Nazarov, Allen Gehret, Robert Shorten +1
Modulus of local continuity is used to evaluate the robustness of neural networks and fairness of their repeated uses in closed-loop models. Here, we revisit a connection between g…
Joint Problems in Learning Multiple Dynamical Systems
Mengjia Niu, Xiaoyu He, Petr Ryšavý +2
Clustering of time series is a well-studied problem, with applications ranging from quantitative, personalized models of metabolism obtained from metabolite concentrations to state…
humancompatible.interconnect: Testing Properties of Repeated Uses of Interconnections of AI Systems
Rodion Nazarov, Anthony Quinn, Robert Shorten +1
Artificial intelligence (AI) systems often interact with multiple agents. The regulation of such AI systems often requires that {\em a priori\/} guarantees of fairness and robustne…