Yang Liu

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Mingyan LiuProfessor of Electrical Engineering and Computer Science, University of MichiganVerified email at umich.edu
David C. ParkesGeorge F. Colony Professor of Computer Science, Harvard UniversityVerified email at eecs.harvard.edu
Armin SarabiAssistant Research Scientist, University of MichiganVerified email at umich.edu
Goran RadanovićResearch Group Leader, Max Planck Institute for Software SystemsVerified email at mpi-sws.org
Berk UstunUCSDVerified email at ucsd.edu
Parinaz NaghizadehAssistant Professor of ISE & ECE, Ohio State UniversityVerified email at osu.edu
Jing ZhangUniversity of MichiganVerified email at umich.edu
Michael Donald BaileyGeorgia Institute of TechnologyVerified email at gatech.edu
Yiling ChenHarvard UniversityVerified email at seas.harvard.edu
Ji LiuStony Brook UniversityVerified email at stonybrook.edu
Christos DimitrakakisProfessor, University of NeuchatelVerified email at alumni.epfl.ch
Chien-Ju HoWashington University in St. LouisVerified email at wustl.edu
Bo LiUniversity of Illinois at Urbana–ChampaignVerified email at illinois.edu
Tamer BaşarSwanlund Endowed Chair Emeritus & CAS Professor Emeritus of ECE, University of IllinoisVerified email at illinois.edu
Yitao LiangAssistant Professor, Peking UniversityVerified email at pku.edu.cn
Jie ZhangProfessor of Computer Science and Engineering, Nanyang Technological UniversityVerified email at ntu.edu.sg
Jing DengProfessor of Computer Science, UNC GreensboroVerified email at uncg.edu
Tudor DumitrasAssistant Professor, University of Maryland, College ParkVerified email at umiacs.umd.edu
Chaowei XiaoAssistant professor at ASUVerified email at umich.edu
Sahand AhmadDirector of Systematic Trading StrategiesVerified email at umich.edu

Yang Liu

Computer Science and Engineering, UC Santa Cruz

Verified email at ucsc.edu - Homepage

weakly supervised learning algorithmic fairness machine learning incentive and consensus


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Actionable recourse in linear classification B Ustun, A Spangher, Y Liu ACM Conference on Fairness, Accountability, and Transparency, 2019	400	2019
Cloudy with a chance of breach: Forecasting cyber security incidents Y Liu, A Sarabi, J Zhang, P Naghizadeh, M Karir, M Bailey, M Liu 24th USENIX security symposium, 1009-1024, 2015	213	2015
How do fairness definitions fare? Testing public attitudes towards three algorithmic definitions of fairness in loan allocations NA Saxena, K Huang, E DeFilippis, G Radanovic, DC Parkes, Y Liu AAAI Conference on AI, Ethics, and Society, 2019	187*	2019
Peer loss functions: Learning from noisy labels without knowing noise rates Y Liu, H Guo International conference on machine learning, 6226-6236, 2020	147	2020
Rating network security posture and comparing network maliciousness M Liu, M Bailey, M Karir, Y Liu, J Zhang US Patent 10,038,703, 2018	111	2018
Learning with instance-dependent label noise: A sample sieve approach H Cheng, Z Zhu, X Li, Y Gong, X Sun, Y Liu International Conference on Learning Representations (ICLR), 2021	102	2021
Calibrated fairness in bandits Y Liu, G Radanovic, C Dimitrakakis, D Mandal, DC Parkes Fairness, Accountability, and Transparency in Machine Learning (FAT-ML), 2017	101	2017
Fairness without harm: Decoupled classifiers with preference guarantees B Ustun, Y Liu, D Parkes International Conference on Machine Learning, 6373-6382, 2019	94	2019
An online learning approach to improving the quality of crowdsourcing Y Liu, M Liu ACM SIGMETRICS, 2015	83	2015
Reinforcement learning with perturbed rewards J Wang, Y Liu, B Li Proceedings of the AAAI conference on artificial intelligence 34 (04), 6202-6209, 2020	79	2020
Learning with noisy labels revisited: A study using real-world human annotations J Wei, Z Zhu, H Cheng, T Liu, G Niu, Y Liu International Conference on Learning Representations, 2021	70	2021
A second-order approach to learning with instance-dependent label noise Z Zhu, T Liu, Y Liu Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021	70	2021
Fair Classification with Group-Dependent Label Noise J Wang, Y Liu*, C Levy ACM Conference on Fairness, Accountability, and Transparency, 2021	62	2021
Risky business: Fine-grained data breach prediction using business profiles A Sarabi, P Naghizadeh, Y Liu, M Liu Journal of Cybersecurity 2 (1), 15-28, 2016	58*	2016
Federated bandit: A gossiping approach Z Zhu, J Zhu, J Liu, Y Liu Proceedings of the 2021 ACM SIGMETRICS/International Conference on …, 2021	53	2021
Surrogate scoring rules Y Liu, J Wang, Y Chen ACM Transactions on Economics and Computation 10 (3), 1-36, 2023	52	2023
Grinding the Space: Learning to Classify Against Strategic Agents Y Chen, Y Liu, C Podimata Advances in Neural Information Processing Systems (NeurIPS), 2020	52*	2020
Learning to incentivize: Eliciting effort via output agreement Y Liu, Y Chen International Joint Conferences on Artificial Intelligence (IJCAI), 2016	51	2016
How do fair decisions fare in long-term qualification? X Zhang, R Tu, Y Liu, M Liu, H Kjellstrom, K Zhang, C Zhang Advances in Neural Information Processing Systems 33, 18457-18469, 2020	50	2020
Machine-learning aided peer prediction Y Liu, Y Chen ACM Conference on Economics and Computation, 63-80, 2017	49	2017

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