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Found 4 papers, 2 papers with code
Supporting Data-Frame Dynamics in AI-assisted Decision Making
High stakes decision-making often requires a continuous interplay between evolving evidence and shifting hypotheses, a dynamic that is not well supported by current AI decision support systems.
Label-Agnostic Forgetting: A Supervision-Free Unlearning in Deep Models
Leveraging this approximation, we adapt the original model to eliminate information from the forgotten data at the representation level.
CaMU: Disentangling Causal Effects in Deep Model Unlearning
To address this shortcoming, the present study undertakes a causal analysis of the unlearning and introduces a novel framework termed Causal Machine Unlearning (CaMU).
Representing and Discovering Adversarial Team Behaviors Using Player Roles
In this paper, we describe a method to represent and discover adversarial group behavior in a continuous domain.
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