23 citations · 44 across the 8 of their papers we have counts for
Showing 2021Show all
3 papers · 1 filter
cs.CY2021
Models of fairness in federated learning
Kate Donahue, Jon Kleinberg
In many real-world situations, data is distributed across multiple self-interested agents. These agents can collaborate to build a machine learning model based on data from multipl…
cs.GT2021★ 14 cited
Optimality and Stability in Federated Learning: A Game-theoretic Approach
Kate Donahue, Jon Kleinberg
Federated learning is a distributed learning paradigm where multiple agents, each only with access to local data, jointly learn a global model. There has recently been an explosion…
cs.GT2021★ 1 cited
Better Together? How Externalities of Size Complicate Notions of Solidarity and Actuarial Fairness
Kate Donahue, Solon Barocas
Consider a cost-sharing game with players of different contribution to the total cost: an example might be an insurance company calculating premiums for a population of mixed-risk…