Liu, Yang

2020
Nripsuta Ani Saxena, Karen Huang, Evan DeFilippis, Goran Radanovic, Yang Liu, and David C. Parkes. 2020. “How do fairness definitions fare? testing public attitudes towards three algorithmic definitions of fairness in loan allocations.” Artificial Intelligence, 283, 103238. Download
Nripsuta Ani Saxena, Karen Huang, Evan DeFilippis, Goran Radanovic, David C. Parkes, and Yang Liu. 2020. “How do fairness definitions fare? Testing public attitudes towards three algorithmic definitions of fairness in loan allocations.” Artificial Intelligence, 283, 103238 . Download
Yiling Chen, Yang Liu, and Chara Podimata. 2020. “Learning Strategy-Aware Linear Classifiers.” In In Proceedings of the Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS 2020). Download
Yang Liu, Juntao Wang, and Yiling Chen. 2020. “Surrogate Scoring Rules.” In Proceedings of the Twenty-first ACM Conference on Economics and Computation. (EC '20). Download
2019
Berk Ustun, Alexander Spanghler, and Yang Liu. 2019. “Actionable Recourse in Linear Classification.” In ACM Conference on Fairness, Accountability, and Transparency (FAT '19). Download
Christos Dimitrakakis, Yang Liu, David C. Parkes, and Goran Radanovic. 2019. “Bayesian Fairness.” In Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI). Download
Nripsuta Saxena, Karen Huang, Evan DeFilippis, Goran Radanovic, David Parkes, and Yang Liu. 2019. “How Do Fairness Definitions Fare? Examining Public Attitudes Towards Algorithmic Definitions of Fairness.” In Proceedings of AI Ethics and Society (AIES) , Pp. 99-106. Download
Yiling Chen, Yang Liu, and Juntao Wang. 2019. “Randomized Wagering Mechanisms.” In Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19) . Download
2018
Shuran Zheng, Bo Waggoner, Yang Liu, and Yiling Chen. 2018. “Active Information Acquisition for Linear Optimization.” In Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI-2018). Download
2017
Yang Liu, Goran Radanovic, Christos Dimitrakakis, Debmalya Mandal, and David C. Parkes. 2017. “Calibrated fairness in Bandits.” In Proceedings of the 4th Workshop on Fairness, Accountability, and Transparency in Machine Learning (Fat/ML 2017). Download
Yang Liu, Goran Radanovic, Christos Dimitrakakis, Debmalya Mandal, and David C. Parkes. 2017. “Fair Experimentation.” In Conference on Digital Experimentation (CODE).
Yang Liu. 2017. “Fair Optimal Stopping Policy for Matching with Mediator.” In Proc. of the Conference on Uncertainty in Artificial Intelligence (UAI-2017). Download
Liu Yang and Yiling Chen. 2017. “Machine Learning aided Peer Prediction.” In Proceedings of the 18th ACM Conference on Economics and Computation (EC-2017). Download
Yang Liu and Yiling Chen. 2017. “Sequential Peer Prediction: Learning to Elicit Effort using Posted Prices.” In Proc. of The Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17) . Download
2016
Yiling Chen and Yang Liu. 12/2016. “A Bandit Framework for Strategic Regression.” In Proc. of the 30th Annual Conference on Neural Information Processing Systems (NIPS). Barcelona, Spain.
Yang Liu and Yiling Chen. 7/2016. “Learning to Incentivize: Eliciting Effort via Output Agreement.” In Proc. of the 25th International Joint Conference on Artificial Intelligence (IJCAI), Pp. 3782-3788. New York, NY. Download