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Multi-Criteria Comparison as a Method of Advancing Knowledge-Guided Machine Learning
This paper describes a generalizable model evaluation method that can be adapted to evaluate AI/ML models across multiple criteria including core scientific principles and more practical outcomes.
Modeling Voters in Multi-Winner Approval Voting
In multi-winner approval voting (AV), an agent submits a ballot consisting of approvals for as many candidates as they wish, and winners are chosen by tallying up the votes and choosing the top-$k$ candidates receiving the most approvals.
On Interactive Machine Learning and the Potential of Cognitive Feedback
Furthermore, we address several of the shortcomings of interactive machine learning by discussing how cognitive feedback may inform features, data, and results in the state of the art.
Heuristic Strategies in Uncertain Approval Voting Environments
In real world voting scenarios, people often do not have complete information about other voter preferences and it can be computationally complex to identify a strategy that will maximize their expected utility.
Heuristics in Multi-Winner Approval Voting
In multi-winner approval voting (AV), an agent may vote for as many candidates as they wish.
