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2020 – today
- 2022
[i8]Xiao Han, Lu Zhang, Yongkai Wu, Shuhan Yuan:
On Interpretable Anomaly Detection Using Causal Algorithmic Recourse. CoRR abs/2212.04031 (2022)- 2021
- [c16]Yaowei Hu, Yongkai Wu, Lu Zhang, Xintao Wu:
A Generative Adversarial Framework for Bounding Confounded Causal Effects. AAAI 2021: 12104-12112 - 2020
- [c15]Yaowei Hu, Yongkai Wu, Lu Zhang, Xintao Wu:
Fair Multiple Decision Making Through Soft Interventions. NeurIPS 2020 - [c14]Wen Huang
, Yongkai Wu, Xintao Wu:
Multi-cause Discrimination Analysis Using Potential Outcomes. SBP-BRiMS 2020: 224-234 - [c13]Wen Huang, Yongkai Wu, Lu Zhang, Xintao Wu:
Fairness through Equality of Effort. WWW (Companion Volume) 2020: 743-751
2010 – 2019
- 2019
- [j1]Lu Zhang, Yongkai Wu, Xintao Wu:
Causal Modeling-Based Discrimination Discovery and Removal: Criteria, Bounds, and Algorithms. IEEE Trans. Knowl. Data Eng. 31(11): 2035-2050 (2019) - [c12]Yongkai Wu, Lu Zhang, Xintao Wu:
Counterfactual Fairness: Unidentification, Bound and Algorithm. IJCAI 2019: 1438-1444 - [c11]Depeng Xu, Yongkai Wu, Shuhan Yuan, Lu Zhang, Xintao Wu:
Achieving Causal Fairness through Generative Adversarial Networks. IJCAI 2019: 1452-1458 - [c10]Yongkai Wu, Lu Zhang, Xintao Wu, Hanghang Tong:
PC-Fairness: A Unified Framework for Measuring Causality-based Fairness. NeurIPS 2019: 3399-3409 - [c9]Yongkai Wu, Lu Zhang, Xintao Wu:
On Convexity and Bounds of Fairness-aware Classification. WWW 2019: 3356-3362 - [i7]Yongkai Wu, Lu Zhang, Xintao Wu, Hanghang Tong:
PC-Fairness: A Unified Framework for Measuring Causality-based Fairness. CoRR abs/1910.12586 (2019) - [i6]Wen Huang, Yongkai Wu, Lu Zhang, Xintao Wu:
Fairness through Equality of Effort. CoRR abs/1911.08292 (2019) - 2018
- [c8]Lu Zhang, Yongkai Wu, Xintao Wu:
Achieving Non-Discrimination in Prediction. IJCAI 2018: 3097-3103 - [c7]Yongkai Wu, Lu Zhang, Xintao Wu:
On Discrimination Discovery and Removal in Ranked Data using Causal Graph. KDD 2018: 2536-2544 - [i5]Yongkai Wu, Lu Zhang, Xintao Wu:
On Discrimination Discovery and Removal in Ranked Data using Causal Graph. CoRR abs/1803.01901 (2018) - [i4]Yongkai Wu, Lu Zhang, Xintao Wu:
Fairness-aware Classification: Criterion, Convexity, and Bounds. CoRR abs/1809.04737 (2018) - 2017
- [c6]Lu Zhang, Yongkai Wu, Xintao Wu:
A Causal Framework for Discovering and Removing Direct and Indirect Discrimination. IJCAI 2017: 3929-3935 - [c5]Lu Zhang, Yongkai Wu, Xintao Wu:
Achieving Non-Discrimination in Data Release. KDD 2017: 1335-1344 - [c4]Srinidhi Katla, Depeng Xu, Yongkai Wu, Qiuping Pan, Xintao Wu:
DPWeka: Achieving Differential Privacy in WEKA. PAC 2017: 184-185 - [i3]Lu Zhang, Yongkai Wu, Xintao Wu:
Achieving non-discrimination in prediction. CoRR abs/1703.00060 (2017) - 2016
- [c3]Yongkai Wu, Xintao Wu:
Using Loglinear Model for Discrimination Discovery and Prevention. DSAA 2016: 110-119 - [c2]Lu Zhang, Yongkai Wu, Xintao Wu:
Situation Testing-Based Discrimination Discovery: A Causal Inference Approach. IJCAI 2016: 2718-2724 - [c1]Lu Zhang, Yongkai Wu, Xintao Wu:
On Discrimination Discovery Using Causal Networks. SBP-BRiMS 2016: 83-93 - [i2]Lu Zhang, Yongkai Wu, Xintao Wu:
Achieving non-discrimination in data release. CoRR abs/1611.07438 (2016) - [i1]Lu Zhang, Yongkai Wu, Xintao Wu:
A causal framework for discovering and removing direct and indirect discrimination. CoRR abs/1611.07509 (2016)
Coauthor Index
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