| Fairgan: Fairness-aware generative adversarial networks D Xu, S Yuan, L Zhang, X Wu 2018 IEEE international conference on big data (big data), 570-575, 2018 | 391 | 2018 |
| A causal framework for discovering and removing direct and indirect discrimination L Zhang, Y Wu, X Wu arXiv preprint arXiv:1611.07509, 2016 | 231 | 2016 |
| Pc-fairness: A unified framework for measuring causality-based fairness Y Wu, L Zhang, X Wu, H Tong Advances in neural information processing systems 32, 2019 | 148 | 2019 |
| Counterfactual fairness: Unidentification, bound and algorithm Y Wu, L Zhang, X Wu Proceedings of the twenty-eighth international joint conference on …, 2019 | 130 | 2019 |
| Achieving causal fairness through generative adversarial networks D Xu, Y Wu, S Yuan, L Zhang, X Wu Proceedings of the Twenty-Eighth International Joint Conference on …, 2019 | 120 | 2019 |
| Achieving non-discrimination in data release L Zhang, Y Wu, X Wu Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge …, 2017 | 89 | 2017 |
| On convexity and bounds of fairness-aware classification Y Wu, L Zhang, X Wu The World Wide Web Conference, 3356-3362, 2019 | 75 | 2019 |
| On discrimination discovery and removal in ranked data using causal graph Y Wu, L Zhang, X Wu Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018 | 67 | 2018 |
| Anti-discrimination learning: a causal modeling-based framework L Zhang, X Wu International Journal of Data Science and Analytics 4, 1-16, 2017 | 66 | 2017 |
| Situation Testing-Based Discrimination Discovery: A Causal Inference Approach. L Zhang, Y Wu, X Wu IJCAI 16, 2718-2724, 2016 | 66 | 2016 |
| Causal modeling-based discrimination discovery and removal: Criteria, bounds, and algorithms L Zhang, Y Wu, X Wu IEEE Transactions on Knowledge and Data Engineering 31 (11), 2035-2050, 2018 | 64 | 2018 |
| FairGAN+: Achieving Fair Data Generation and Classification through Generative Adversarial Nets D Xu, S Yuan, L Zhang, X Wu 2019 IEEE international conference on big data (Big Data), 1401-1406, 2019 | 61 | 2019 |
| Fairness through equality of effort W Huan, Y Wu, L Zhang, X Wu Companion Proceedings of the Web Conference 2020, 743-751, 2020 | 47 | 2020 |
| Achieving non-discrimination in prediction L Zhang, Y Wu, X Wu arXiv preprint arXiv:1703.00060, 2017 | 43 | 2017 |
| A generative adversarial framework for bounding confounded causal effects Y Hu, Y Wu, L Zhang, X Wu Proceedings of the AAAI Conference on Artificial Intelligence 35 (13), 12104 …, 2021 | 36 | 2021 |
| Achieving long-term fairness in sequential decision making Y Hu, L Zhang Proceedings of the AAAI Conference on Artificial Intelligence 36 (9), 9549-9557, 2022 | 29 | 2022 |
| The client assignment problem for continuous distributed interactive applications: Analysis, algorithms, and evaluation L Zhang, X Tang IEEE Transactions on Parallel and Distributed Systems 25 (3), 785-795, 2013 | 29 | 2013 |
| Optimizing client assignment for enhancing interactivity in distributed interactive applications L Zhang, X Tang IEEE/ACM Transactions on Networking 20 (6), 1707-1720, 2012 | 29 | 2012 |
| Client assignment for improving interactivity in distributed interactive applications L Zhang, X Tang 2011 Proceedings IEEE INFOCOM, 3227-3235, 2011 | 28 | 2011 |
| Achieving counterfactual fairness for causal bandit W Huang, L Zhang, X Wu Proceedings of the AAAI conference on artificial intelligence 36 (6), 6952-6959, 2022 | 27 | 2022 |
Xintao WuUniversity of ArkansasBestätigte E-Mail-Adresse bei uark.edu