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of 8
pro vyhledávání: '"Rahmattalabi, Aida"'
Autor:
Rahmattalabi, Aida, Xiang, Alice
In recent years, there has been increasing interest in causal reasoning for designing fair decision-making systems due to its compatibility with legal frameworks, interpretability for human stakeholders, and robustness to spurious correlations inhere
Externí odkaz:
http://arxiv.org/abs/2201.10683
We study the problem of learning, from observational data, fair and interpretable policies that effectively match heterogeneous individuals to scarce resources of different types. We model this problem as a multi-class multi-server queuing system whe
Externí odkaz:
http://arxiv.org/abs/2201.10053
Autor:
Rahmattalabi, Aida, Jabbari, Shahin, Lakkaraju, Himabindu, Vayanos, Phebe, Izenberg, Max, Brown, Ryan, Rice, Eric, Tambe, Milind
Several behavioral, social, and public health interventions, such as suicide/HIV prevention or community preparedness against natural disasters, leverage social network information to maximize outreach. Algorithmic influence maximization techniques h
Externí odkaz:
http://arxiv.org/abs/2006.07906
Autor:
Rahmattalabi, Aida, Vayanos, Phebe, Fulginiti, Anthony, Rice, Eric, Wilder, Bryan, Yadav, Amulya, Tambe, Milind
Publikováno v:
year=2019, pages=15750 to 15761
Fueled by algorithmic advances, AI algorithms are increasingly being deployed in settings subject to unanticipated challenges with complex social effects. Motivated by real-world deployment of AI driven, social-network based suicide prevention and la
Externí odkaz:
http://arxiv.org/abs/2006.06865
Autor:
Rahmattalabi, Aida, Adhikari, Anamika Barman, Vayanos, Phebe, Tambe, Milind, Rice, Eric, Baker, Robin
Substance use and abuse is a significant public health problem in the United States. Group-based intervention programs offer a promising means of preventing and reducing substance abuse. While effective, unfortunately, inappropriate intervention grou
Externí odkaz:
http://arxiv.org/abs/1902.00171
Akademický článek
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Publikováno v:
2016 IEEE/RSJ International Conference on Intelligent Robots & Systems (IROS); 2016, p4424-4429, 6p
Autor:
Izenberg, Maxwell, Brown, Ryan, Siebert, Cora, Heinz, Ron, Rahmattalabi, Aida, Vayanos, Phebe
Publikováno v:
Field Methods; 20220101, Issue: Preprints