Wu, Zhiwei Steven

Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness

Kearns, M., Neel, S., Roth, A., & Wu, Z. S. (2017) · arXiv

Ethics and Social Impacts of AIPrivacy-Preserving Technologies in Data

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Improving Human-AI Partnerships in Child Welfare: Understanding Worker Practices, Challenges, and Desires for Algorithmic Decision Support

Kawakami, A., Sivaraman, V., Cheng, H.-F., Stapleton, L., Cheng, Y., Qing, D., Perer, A., Wu, Z. S., Zhu, H., & Holstein, K. (2022) · CHI Conference on Human Factors in Computing Systems

Ethics and Social Impacts of AIInformation Systems Theories and Implementation

Cited by 143

Exploring How Machine Learning Practitioners (Try To) Use Fairness Toolkits

Deng, W. H., Nagireddy, M., Lee, M. S. A., Singh, J., Wu, Z. S., Holstein, K., & Zhu, H. (2022) · 2022 ACM Conference on Fairness Accountability and Transparency

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 99

All Roads Lead to Likelihood: The Value of Reinforcement Learning in Fine-Tuning

Swamy, G., Choudhury, S., Sun, W., Wu, Z. S., & Bagnell, J. A. (2025) · arXiv

Reinforcement Learning in RoboticsTopic Modeling

Cited by 55

Ground(less) Truth: A Causal Framework for Proxy Labels in Human-Algorithm Decision-Making

Guerdan, L., Coston, A., Wu, Z. S., & Holstein, K. (2023) · 2023 ACM Conference on Fairness, Accountability, and Transparency

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 28

Causal Imitation Learning under Temporally Correlated Noise

Swamy, G., Choudhury, S., Bagnell, J. A., & Wu, Z. S. (2022) · arXiv

Reinforcement Learning in RoboticsMachine Learning and Algorithms

Cited by 9

Privacy for the Protected (Only)

Kearns, M., Roth, A., Wu, Z. S., & Yaroslavtsev, G. (2015) · arXiv

Privacy-Preserving Technologies in DataPrivacy, Security, and Data Protection

Cited by 5