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Found 6 papers, 2 papers with code
Fairness in Forecasting of Observations of Linear Dynamical Systems
We also show that by exploiting sparsity in the convexifications, we can reduce the run time of our methods considerably.
Herd Routes: A Preventative IoT-Based System for Improving Female Pedestrian Safety on City Streets
With positive results from the initial testing of the proof-of-concept, further development could significantly contribute towards creating safer pedestrian routes through cities, and tackle the societal change that is required to improve female pedestrian safety in the long term.
Predictability and Fairness in Load Aggregation and Operations of Virtual Power Plants
We show that even considering the non-linearity of the alternating-current model, this notion of predictability and fairness can be guaranteed for incrementally input-to-state stable (iISS) controllers, under mild assumptions.
Subgroup Fairness in Two-Sided Markets
In the process, we introduce a novel notion of subgroup fairness (which we call Inter-fairness), which can be combined with other notions of fairness within each subgroup (called Intra-fairness), and the utility for the customers (Customer-Care) in the objective of the market-clearing problem.
Predictability and Fairness in Social Sensing
We consider the design of distributed algorithms that govern the manner in which agents contribute to a social sensing platform.
Fairness in Forecasting and Learning Linear Dynamical Systems
In machine learning, training data often capture the behaviour of multiple subgroups of some underlying human population.
