The Client Assignment Problem for Continuous Distributed Interactive Applications. - Lu Zhang 021; Xueyan Tang (ICDCS, 2011)

Client assignment for improving interactivity in distributed interactive applications. - Lu Zhang 021; Xueyan Tang (INFOCOM, 2011)

Optimizing client assignment for enhancing interactivity in distributed interactive applications. - Lu Zhang 021; Xueyan Tang (IEEE/ACM Trans. Netw., 2012)

Brief announcement: on minimum interaction time for continuous distributed interactive computing. - Lu Zhang 021; Xueyan Tang; Bingsheng He (PODC, 2013)

Client assignment problems for distributed interactive computing - Lu Zhang 021 (2013)

The Client Assignment Problem for Continuous Distributed Interactive Applications: Analysis, Algorithms, and Evaluation. - Lu Zhang 021; Xueyan Tang (IEEE Trans. Parallel Distributed Syst., 2014)

Building Bayesian networks from GWAS statistics based on Independence of Causal Influence. - Lu Zhang 021; Qiuping Pan; Xintao Wu; Xinghua Shi (BIBM, 2016)

Situation Testing-Based Discrimination Discovery: A Causal Inference Approach. - Lu Zhang 021; Yongkai Wu; Xintao Wu (IJCAI, 2016)

On Discrimination Discovery Using Causal Networks. - Lu Zhang 021; Yongkai Wu; Xintao Wu (SBP-BRiMS, 2016)

STIP: An SNP-trait inference platform. - Qiuping Pan; Lu Zhang 021; Xintao Wu (BIBM, 2017)

Modeling SNP and quantitative trait association from GWAS catalog using CLG Bayesian network. - Lu Zhang 021; Qiuping Pan; Xintao Wu (BIBM, 2017)

A Causal Framework for Discovering and Removing Direct and Indirect Discrimination. - Lu Zhang 021; Yongkai Wu; Xintao Wu (IJCAI, 2017)

Achieving Non-Discrimination in Data Release. - Lu Zhang 021; Yongkai Wu; Xintao Wu (KDD, 2017)

Anti-discrimination learning: a causal modeling-based framework. - Lu Zhang 021; Xintao Wu (Int. J. Data Sci. Anal., 2017)

Analysis of Minimum Interaction Time for Continuous Distributed Interactive Computing. - Lu Zhang 021; Xueyan Tang; Bingsheng He (IEEE Trans. Parallel Distributed Syst., 2017)

FairGAN: Fairness-aware Generative Adversarial Networks. - Depeng Xu 001; Shuhan Yuan; Lu Zhang 021; Xintao Wu (IEEE BigData, 2018)

Achieving Non-Discrimination in Prediction. - Lu Zhang 021; Yongkai Wu; Xintao Wu (IJCAI, 2018)

On Discrimination Discovery and Removal in Ranked Data using Causal Graph. - Yongkai Wu; Lu Zhang 021; Xintao Wu (KDD, 2018)

Fairness-aware Classification: Criterion, Convexity, and Bounds. - Yongkai Wu; Lu Zhang 021; Xintao Wu (CoRR, 2018)

FairGAN+: Achieving Fair Data Generation and Classification through Generative Adversarial Nets. - Depeng Xu 001; Shuhan Yuan; Lu Zhang 021; Xintao Wu (IEEE BigData, 2019)

Counterfactual Fairness: Unidentification, Bound and Algorithm. - Yongkai Wu; Lu Zhang 021; Xintao Wu (IJCAI, 2019)

Achieving Causal Fairness through Generative Adversarial Networks. - Depeng Xu 001; Yongkai Wu; Shuhan Yuan; Lu Zhang 021; Xintao Wu (IJCAI, 2019)

PC-Fairness: A Unified Framework for Measuring Causality-based Fairness. - Yongkai Wu; Lu Zhang 021; Xintao Wu; Hanghang Tong (NeurIPS, 2019)

On Convexity and Bounds of Fairness-aware Classification. - Yongkai Wu; Lu Zhang 021; Xintao Wu (WWW, 2019)

Bayesian Network Construction and Genotype-Phenotype Inference Using GWAS Statistics. - Lu Zhang 021; Qiuping Pan; Yue Wang 009; Xintao Wu; Xinghua Shi (IEEE ACM Trans. Comput. Biol. Bioinform., 2019)

Causal Modeling-Based Discrimination Discovery and Removal: Criteria, Bounds, and Algorithms. - Lu Zhang 021; Yongkai Wu; Xintao Wu (IEEE Trans. Knowl. Data Eng., 2019)

Fair Multiple Decision Making Through Soft Interventions. - Yaowei Hu 001; Yongkai Wu; Lu Zhang 021; Xintao Wu (NeurIPS, 2020)

Fairness through Equality of Effort. - Wen Huang 003; Yongkai Wu; Lu Zhang 021; Xintao Wu (WWW (Companion Volume), 2020)

A Generative Adversarial Framework for Bounding Confounded Causal Effects. - Yaowei Hu 001; Yongkai Wu; Lu Zhang 021; Xintao Wu (AAAI, 2021)

Discovering Time-invariant Causal Structure from Temporal Data. - Saima Absar; Lu Zhang 021 (CIKM, 2021)

Achieving Long-Term Fairness in Sequential Decision Making. - Yaowei Hu 001; Lu Zhang 021 (AAAI, 2022)

Achieving Counterfactual Fairness for Causal Bandit. - Wen Huang 003; Lu Zhang 021; Xintao Wu (AAAI, 2022)

Generating Textual Adversaries with Minimal Perturbation. - Xingyi Zhao; Lu Zhang 021; Depeng Xu 001; Shuhan Yuan (EMNLP (Findings), 2022)

Robust Hate Speech Detection via Mitigating Spurious Correlations. - Kshitiz Tiwari; Shuhan Yuan; Lu Zhang 021 (AACL/IJCNLP (2), 2022)

Coded Hate Speech Detection via Contextual Information. - Depeng Xu 001; Shuhan Yuan; Yueyang Wang; Angela Uchechukwu Nwude; Lu Zhang 021; Anna Zajicek; Xintao Wu (PAKDD (1), 2022)

On Interpretable Anomaly Detection Using Causal Algorithmic Recourse. - Xiao Han 008; Lu Zhang 021; Yongkai Wu; Shuhan Yuan (CoRR, 2022)

Striking a Balance in Fairness for Dynamic Systems Through Reinforcement Learning. - Yaowei Hu 001; Jacob Lear; Lu Zhang 021 (IEEE Big Data, 2023)

On Root Cause Localization and Anomaly Mitigation through Causal Inference. - Xiao Han 008; Lu Zhang 021; Yongkai Wu; Shuhan Yuan (CIKM, 2023)

Neural Time-Invariant Causal Discovery from Time Series Data. - Saima Absar; Yongkai Wu; Lu Zhang 021 (IJCNN, 2023)

Achieving Counterfactual Fairness for Anomaly Detection. - Xiao Han 008; Lu Zhang 021; Yongkai Wu; Shuhan Yuan (PAKDD (1), 2023)

Algorithmic Recourse for Anomaly Detection in Multivariate Time Series. - Xiao Han 008; Lu Zhang 021; Yongkai Wu; Shuhan Yuan (CoRR, 2023)

Long-Term Fair Decision Making through Deep Generative Models. - Yaowei Hu 001; Yongkai Wu; Lu Zhang 021 (AAAI, 2024)

Time Series Causal Discovery Using a Hybrid Method. - Saima Absar; Lu Zhang 021 (IEEE Big Data, 2024)

Fair Weak-Supervised Learning: A Multiple-Instance Learning Approach. - Yucong Dai; Xiangyu Jiang; Yaowei Hu 001; Lu Zhang 021; Yongkai Wu (IJCNN, 2024)

Implications of Minimum Description Length for Adversarial Attack in Natural Language Processing. - Kshitiz Tiwari; Lu Zhang 021 (Entropy, 2024)

A Causal Lens for Learning Long-term Fair Policies. - Jacob Lear; Lu Zhang 021 (ICLR, 2025)

Causally Fair Node Classification on Non-IID Graph Data. - Yucong Dai; Lu Zhang 021; Yaowei Hu 001; Susan Gauch; Yongkai Wu (CoRR, 2025)