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Found 6 papers, 1 papers with code
Discovering Optimal Scoring Mechanisms in Causal Strategic Prediction
While earlier works cast these manipulations as undesirable gaming, recent works have adopted a more nuanced causal framing in which manipulations can improve outcomes of interest, and setting coherent mechanisms requires accounting for both predictive accuracy and improvement of the outcome.
Active Fairness Auditing
The fast spreading adoption of machine learning (ML) by companies across industries poses significant regulatory challenges.
Margin-distancing for safe model explanation
The growing use of machine learning models in consequential settings has highlighted an important and seemingly irreconcilable tension between transparency and vulnerability to gaming.
Revenue maximization via machine learning with noisy data
We conclude with an application of our guarantees to multi-task mechanism design, where there are multiple distributions over buyers' values and the goal is to learn a high-revenue mechanism per distribution.
Evaluating and Rewarding Teamwork Using Cooperative Game Abstractions
We apply our methods to study teams of artificial RL agents as well as real world teams from professional sports.
Moments in Time Dataset: one million videos for event understanding
We present the Moments in Time Dataset, a large-scale human-annotated collection of one million short videos corresponding to dynamic events unfolding within three seconds.
