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Journal Articles
- 2024
[j3]Jiongli Zhu, Babak Salimi:
Overcoming Data Biases: Towards Enhanced Accuracy and Reliability in Machine Learning. IEEE Data Eng. Bull. 47(1): 18-35 (2024)- 2023
- [j2]Chenhao Lin, Sicong Han
, Jiongli Zhu, Qian Li, Chao Shen, Youwei Zhang, Xiaohong Guan:
Sensitive region-aware black-box adversarial attacks. Inf. Sci. 637: 118929 (2023) - [j1]Jiongli Zhu, Sainyam Galhotra, Nazanin Sabri, Babak Salimi:
Consistent Range Approximation for Fair Predictive Modeling. Proc. VLDB Endow. 16(11): 2925-2938 (2023)
Conference and Workshop Papers
- 2022
- [c3]Romila Pradhan, Jiongli Zhu, Boris Glavic, Babak Salimi:
Interpretable Data-Based Explanations for Fairness Debugging. SIGMOD Conference 2022: 247-261 - [c2]Jiongli Zhu, Romila Pradhan, Boris Glavic, Babak Salimi:
Generating Interpretable Data-Based Explanations for Fairness Debugging using Gopher. SIGMOD Conference 2022: 2433-2436 - 2021
- [c1]Rundong Li, Pinghui Wang, Jiongli Zhu, Junzhou Zhao, Jia Di, Xiaofei Yang, Kai Ye:
Building Fast and Compact Sketches for Approximately Multi-Set Multi-Membership Querying. SIGMOD Conference 2021: 1077-1089
Informal and Other Publications
- 2024
- [i3]Jiongli Zhu, Su Feng, Boris Glavic, Babak Salimi:
Learning from Uncertain Data: From Possible Worlds to Possible Models. CoRR abs/2405.18549 (2024) - 2022
- [i2]Jiongli Zhu, Nazanin Sabri, Sainyam Galhotra, Babak Salimi:
Crab: Learning Certifiably Fair Predictive Models in the Presence of Selection Bias. CoRR abs/2212.10839 (2022) - 2021
- [i1]Romila Pradhan, Jiongli Zhu, Boris Glavic, Babak Salimi:
Interpretable Data-Based Explanations for Fairness Debugging. CoRR abs/2112.09745 (2021)
Coauthor Index
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