Kenthapadi, Krishnaram

Our Data, Ourselves: Privacy Via Distributed Noise Generation

Dwork, C., Kenthapadi, K., McSherry, F., Mironov, I., & Naor, M. (2006) · Lecture Notes in Computer Science

Cryptography and Data SecurityPrivacy-Preserving Technologies in Data

Cited by 1,835

Bias in Bios: A Case Study of Semantic Representation Bias in a High-Stakes Setting

De-Arteaga, M., Romanov, A., Wallach, H., Chayes, J., Borgs, C., Chouldechova, A., Geyik, S., Kenthapadi, K., & Kalai, A. T. (2019) · arXiv

Ethics and Social Impacts of AINames, Identity, and Discrimination Research

Cited by 337

Bias in Bios: A Case Study of Semantic Representation Bias in a High-Stakes Setting

De-Arteaga, M., Romanov, A., Wallach, H., Chayes, J., Borgs, C., Chouldechova, A., Geyik, S., Kenthapadi, K., & Kalai, A. T. (2019) · Proceedings of the Conference on Fairness, Accountability, and Transparency

Ethics and Social Impacts of AINames, Identity, and Discrimination Research

Cited by 337

Minimax group fairness: algorithms and experiments

Diana, E., Gill, W., Kearns, M., Kenthapadi, K., & Roth, A. (2021) · Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society

Ethics and Social Impacts of AIPrivacy-Preserving Technologies in Data

Cited by 74

Fair Bayesian Optimization

Perrone, V., Donini, M., Zafar, M. B., Schmucker, R., Kenthapadi, K., & Archambeau, C. (2021) · Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society

Ethics and Social Impacts of AIAdvanced Bandit Algorithms Research

Cited by 66

Explainable AI in Industry: Practical Challenges and Lessons Learned

Gade, K., Geyik, S., Kenthapadi, K., Mithal, V., & Taly, A. (2020) · Companion Proceedings of the Web Conference 2020

Explainable Artificial Intelligence (XAI)Ethics and Social Impacts of AI

Cited by 46

Towards Unbiased and Accurate Deferral to Multiple Experts

Keswani, V., Lease, M., & Kenthapadi, K. (2021) · Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society

Ethics and Social Impacts of AIMachine Learning and Algorithms

Cited by 45

Grounding and Evaluation for Large Language Models: Practical Challenges and Lessons Learned (Survey)

Kenthapadi, K., Sameki, M., & Taly, A. (2024) · Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining

Ethics and Social Impacts of AIAdversarial Robustness in Machine Learning

Cited by 36

Human-Algorithm Collaboration: Achieving Complementarity and Avoiding Unfairness

Donahue, K., Chouldechova, A., & Kenthapadi, K. (2022) · 2022 ACM Conference on Fairness Accountability and Transparency

Ethics and Social Impacts of AIMachine Learning and Algorithms

Cited by 33