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Yang Liu
Yang Liu
Computer Science and Engineering, UC Santa Cruz
在 ucsc.edu 的电子邮件经过验证 - 首页
标题
引用次数
引用次数
年份
Actionable recourse in linear classification
B Ustun, A Spangher, Y Liu
ACM Conference on Fairness, Accountability, and Transparency, 2019
4082019
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
325*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
189*2019
Peer loss functions: Learning from noisy labels without knowing noise rates
Y Liu, H Guo
International conference on machine learning, 6226-6236, 2020
1512020
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
1052021
Calibrated fairness in bandits
Y Liu, G Radanovic, C Dimitrakakis, D Mandal, DC Parkes
Fairness, Accountability, and Transparency in Machine Learning (FAT-ML), 2017
1022017
Fairness without harm: Decoupled classifiers with preference guarantees
B Ustun, Y Liu, D Parkes
International Conference on Machine Learning, 6373-6382, 2019
962019
An online learning approach to improving the quality of crowdsourcing
Y Liu, M Liu
ACM SIGMETRICS, 2015
832015
Reinforcement learning with perturbed rewards
J Wang, Y Liu, B Li
Proceedings of the AAAI conference on artificial intelligence 34 (04), 6202-6209, 2020
802020
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
762021
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
722021
Fair Classification with Group-Dependent Label Noise
J Wang, Y Liu*, C Levy
ACM Conference on Fairness, Accountability, and Transparency, 2021
622021
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
Grinding the Space: Learning to Classify Against Strategic Agents
Y Chen, Y Liu, C Podimata
Advances in Neural Information Processing Systems (NeurIPS), 2020
55*2020
Federated bandit: A gossiping approach
Z Zhu, J Zhu, J Liu, Y Liu
Proceedings of the 2021 ACM SIGMETRICS/International Conference on …, 2021
542021
Surrogate scoring rules
Y Liu, J Wang, Y Chen
ACM Transactions on Economics and Computation 10 (3), 1-36, 2023
532023
Learning to incentivize: Eliciting effort via output agreement
Y Liu, Y Chen
International Joint Conferences on Artificial Intelligence (IJCAI), 2016
512016
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
502020
Machine-learning aided peer prediction
Y Liu, Y Chen
ACM Conference on Economics and Computation, 63-80, 2017
492017
Sequential peer prediction: Learning to elicit effort using posted prices
Y Liu, Y Chen
Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017
472017
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