Lu Zhang
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Publications

  1. A Causal Lens for Learning Long-term Fair Policies
    Jacob Lear and Lu Zhang
    Proceedings of the Thirteenth International Conference on Learning Representations (ICLR), 2025.

  2. Root Cause Analysis of Anomalies in Multivariate Time Series Through Granger Causal Discovery
    Xiao Han, Saima Absar, Lu Zhang, and Shuhan Yuan
    Proceedings of the Thirteenth International Conference on Learning Representations (ICLR), 2025.

  3. Neural-HATS: Neural Hybrid Approach for Time Series Causal Discover
    Saima Absar, Wen Huang, Yongkai Wu, and Lu Zhang
    Artificial Intelligence for Time Series Analysis (AI4TS): Theory, Algorithms, and Applications Workshop, AAAI'25, 2025.

  4. Fair Weak-Supervised Learning: A Multiple-Instance Learning Approach
    Yucong Dai, Xiangyu Jiang, Yaowei Hu, Lu Zhang, and Yongkai Wu
    Proceedings of the 2024 International Joint Conference on Neural Networks (IJCNN), 2024.

  5. Implications of Minimum Description Length for Adversarial Attack in Natural Language Processing
    Kshitiz Tiwari and Lu Zhang
    Entropy, 26 (5), 354, 2024.

  6. Long-term Fair Decision Making Through Deep Generative Models
    Yaowei Hu, Yongkai Wu, and Lu Zhang
    Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI), February 20-27, 2024.

  7. Striking a Balance in Fairness for Dynamic Systems Through Reinforcement Learning
    Yaowei Hu, Jacob Lear, and Lu Zhang
    Proceedings of the 2023 IEEE International Conference on Big Data, December 15-18, 2023.

  8. On Root Cause Localization and Anomaly Mitigation through Causal Inference
    Xiao Han, Lu Zhang, Yongkai Wu, and Shuhan Yuan
    Proceedings of the 32nd ACM International Conference on Information and Knowledge Management (CIKM), October 21-25, 2023.

  9. Neural Time-Invariant Causal Discovery from Time Series Data
    Saima Absar and Lu Zhang
    Proceedings of International Joint Conference on Neural Networks (IJCNN), June 18-23, 2023.

  10. Achieving Counterfactual Fairness for Anomaly Detection
    Xiao Han, Lu Zhang, Yongkai Wu, and Shuhan Yuan
    Proceedings of the 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), May 25-28, 2023.

  11. Textual Adversarial Attacking as Combinatorial Optimization in a Reduced Search Space
    Xingyi Zhao, Lu Zhang, Depeng Xu, and Shuhan Yuan
    Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP), Short Paper Track, 2022.

  12. Robust Hate Speech Detection via Mitigating Spurious Correlations
    Kshitiz Tiwari, Shuhan Yuan, and Lu Zhang
    Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing (AACL-IJCNLP), Short Paper Track, 2022.

  13. Coded Hate Speech Detection via Contextual Information
    Depeng Xu, Shuhan Yuan, Yueyang Wang, Angela Uchechukwu Nwude, Lu Zhang, Anna Zajicek, and Xintao Wu
    Proceedings of the 26th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2022.

  14. Achieving Long-term Fairness in Sequential Decision Making
    Yaowei Hu and Lu Zhang
    Proceedings of the 36th AAAI Conference on Artificial Intelligence (AAAI), 2022.

  15. Achieving Counterfactual Fairness for Causal Bandit
    Wen Huang, Lu Zhang and Xintao Wu
    Proceedings of the 36th AAAI Conference on Artificial Intelligence (AAAI), 2022.

  16. An Exploratory Study on Fairness-Aware Design Decision-Making
    Sumaiya Sultana Tanu, Lu Zhang, Dinesh Gauri and Zhenghui Sha
    Proceedings of the Hawai'i International Conference on System Sciences, 2022.

  17. Achieving Counterfactual Fairness for Causal Bandit
    Wen Huang, Lu Zhang and Xintao Wu
    NeurIPS2021 workshop, Algorithmic Fairness through the Lens of Causality and Robustness (AFCR), 2021.

  18. Discovering Time-invariant Causal Structure From Temporal Data
    Saima Absar and Lu Zhang
    Proceeding of the 30th ACM International Conference on Information and Knowledge Management (CIKM), Short Paper Track, 2021.

  19. A Generative Adversarial Framework for Bounding Confounded Causal Effects
    Yaowei Hu, Yongkai Wu, Lu Zhang and Xintao Wu
    Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI), 2021.

  20. Fair Multiple Decision Making Through Soft Interventions
    Yaowei Hu, Yongkai Wu, Lu Zhang and Xintao Wu
    Proceedings of the 34th Conference on Neural Information Processing Systems (NeurIPS), 2020.

  21. Fairness Through Equality of Effort
    Wen Huang, Yongkai Wu, Lu Zhang and Xintao Wu
    Proceedings of the WWW Workshop on Fairness, Accountability, Transparency, Ethics and Society on the Web, Taipei, April 21, 2020.

  22. PC-Fairness: A Unified Framework for Measuring Causality-based Fairness
    Yongkai Wu, Lu Zhang, Xintao Wu and Hanghang Tong
    Proceedings of the 33rd Conference on Neural Information Processing Systems (NeurIPS), 2019.

  23. Counterfactual Fairness: Unidentification, Bound and Algorithm
    Yongkai Wu, Lu Zhang and Xintao Wu
    Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), 2019.

  24. Achieving Causal Fairness through Generative Adversarial Networks
    Depeng Xu, Yongkai Wu, Shuhan Yuan, Lu Zhang and Xintao Wu
    Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), 2019.

  25. FairGAN+: Achieving Fair Data Generation and Fair Classification through Generative Adversarial Networks
    Depeng Xu, Shuhan Yuan, Lu Zhang and Xintao Wu
    Proceedings of the KDD 2019 Workshop on Explainable AI for Fairness, Accountability & Transparency (XAI), 2019.

  26. On Convexity and Bounds of Fairness-aware Classification
    Yongkai Wu, Lu Zhang and Xintao Wu
    The WEB Conference (formerly WWW), 2019.

  27. FairGAN: Fairness-aware Generative Adversarial Networks
    Depeng Xu, Shuhan Yuan, Lu Zhang and Xintao Wu
    IEEE Big Data, 2018.

  28. Causal Modeling-based Approach for Direct and Indirect Discrimination: Criteria, Bound, and Algorithm
    Lu Zhang, Yongkai Wu and Xintao Wu
    IEEE Transactions on Knowledge and Data Engineering, 2018.

  29. On Discrimination Discovery and Removal in Ranked Data Using Causal Graph
    Yongkai Wu, Lu Zhang and Xintao Wu
    ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD’18), 2018.

  30. Achieving Non-discrimination in Prediction
    Lu Zhang, Yongkai Wu and Xintao Wu
    International Joint Conference on Artificial Intelligence (IJCAI’18), 2018.

  31. Modeling SNP and Quantitative Trait Association From GWAS Catalog Using CLG Bayesian Network
    Lu Zhang, Qiuping Pan and Xintao Wu
    IEEE International Conference on Bioinformatics and Biomedicine (BIBM’17), 2017.

  32. STIP: An SNP-Trait Inference Platform
    Qiuping Pan, Lu Zhang and Xintao Wu
    IEEE International Conference on Bioinformatics and Biomedicine (BIBM’17), Demo Track, 2017.

  33. Achieving Non-discrimination in Data Release
    Lu Zhang, Yongkai Wu and Xintao Wu
    ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD’17), pp.1335-1344, 2017.

  34. A Causal Framework for Discovering and Removing Direct and Indirect Discrimination
    Lu Zhang, Yongkai Wu and Xintao Wu
    International Joint Conference on Artificial Intelligence (IJCAI’17), pp.3929-3935, 2017.

  35. Bayesian Network Construction and Genotype-phenotype Inference Using GWAS Statistics
    Lu Zhang, Qiuping Pan, Yue Wang, Xintao Wu and Xinghua Shi
    IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2017.

  36. Anti-discrimination Learning: A Causal Modeling-based Framework
    Lu Zhang and Xintao Wu
    International Journal of Data Science and Analytics, vol.4, no.1, pp.1-16, Aug. 2017.

  37. Analysis of Minimum Interaction Time for Continuous Distributed Interactive Computing
    Lu Zhang, Xueyan Tang and Bingsheng He
    IEEE Transactions on Parallel and Distributed Systems, vol.28, no.2, pp.401-415, Feb. 2017.

  38. Building Bayesian Networks From GWAS Statistics Based on Independence of Causal Influence
    Lu Zhang, Qiuping Pan, Xintao Wu and Xinghua Shi
    IEEE International Conference on Bioinformatics and Biomedicine (BIBM’16), pp.529-532, 2016.

  39. Situation Testing-based Discrimination Discovery: A Causal Inference Approach
    Lu Zhang, Yongkai Wu and Xintao Wu
    International Joint Conference on Artificial Intelligence (IJCAI’16), pp.2718-2724, 2016.

  40. On Discrimination Discovery Using Causal Networks
    Lu Zhang, Yongkai Wu and Xintao Wu
    International Conference on Social Computing, Behavioral-Cultural Modeling & Prediction and Behavior Representation in Modeling and Simulation (SBP-BRiMS’16), pp.83-93, 2016.

  41. Brief Announcement: On Minimum Interaction Time for Continuous Distributed Interactive Computing
    Lu Zhang, Xueyan Tang and Bingsheng He
    ACM symposium on Principles of distributed computing (PODC’13), pp.122-124, 2013.

  42. The Client Assignment Problem for Continuous Distributed Interactive Applications
    Lu Zhang and Xueyan Tang
    International Conference on Distributed Computing Systems (ICDCS’11), pp.203-214, 2011.

  43. Client Assignment for Improving Interactivity in Distributed Interactive Applications
    Lu Zhang and Xueyan Tang
    IEEE International Conference on Computer Communications (INFOCOM’11), pp.3227-3235, 2011.

  44. The Client Assignment Problem for Continuous Distributed Interactive Applications: Analysis, Algorithms, and Evaluation
    Lu Zhang and Xueyan Tang
    IEEE Transactions on Parallel and Distributed Systems, vol.25, no.3, pp.785-795, Mar. 2014.

  45. Optimizing Client Assignment for Enhancing Interactivity in Distributed Interactive Applications
    Lu Zhang and Xueyan Tang
    IEEE/ACM Transactions on Networking, vol.20, no.6, pp.1707-1720, Dec. 2012.