Here is my Google Scholar page.

2024

  • Performative Federated Learning: A Solution to Model-Dependent and Heterogeneous Distribution Shifts.
    K. Jin, T. Yin, Z. Chen, Z. Sun, X. Zhang, Y. Liu and M. Liu
    In the 38th AAAI Conference on Artificial Intelligence (AAAI), 2024.
    pdf

2023

  • Counterfactually Fair Representation
    Z. Zuo, M. Khalili and X. Zhang
    In the 37th Conference on Neural Information Processing Systems (NeurIPS), 2023.
    pdf

  • Loss Balancing for Fair Supervised Learning
    M. Khalili, X. Zhang and M. Abroshan
    In 40th International Conference on Machine Learning (ICML), 2023.
    pdf

  • Fairness and Accuracy under Domain Generalization
    T. Pham, X. Zhang and P. Zhang
    In 11th International Conference on Learning Representations (ICLR), 2023.
    pdf

2022

  • A Fair and Interpretable Network for Clinical Risk Prediction: A Regularized Multi-view Multi-task Learning Approach
    T. Pham, C. Yin, L. Mehta, X. Zhang and P. Zhang
    In Knowledge and Information Systems (KAIS), 2022.
    pdf

  • Fairness Interventions as (Dis)incentives for Strategic Manipulation
    X. Zhang, M. Khalili, K. Jin, P. Naghizadeh and M. Liu
    In the 39th International Conference on Machine Learning (ICML), 2022.
    pdf
    poster
    slides

  • Incentive Mechanisms for Strategic Classification and Regression Problems
    K. Jin, X. Zhang, M. Khalili, P. Naghizadeh and M. Liu
    In ACM Conference on Economics and Computation, (EC), 2022.
    Contributed Talk in ICLR Workshop on Socially Responsible Machine Learning, 2022.
    pdf

  • Differentially Private Real-Time Release of Sequential Data
    X. Zhang, M. Khalili and M. Liu
    ACM Transactions on Privacy and Security (TOPS), 2022.
    pdf

2021

  • Fair Sequential Selection Using Supervised Learning Models
    M. Khalili, X. Zhang and M. Abroshan
    In the 35th Conference on Neural Information Processing Systems (NeurIPS), 2021.
    pdf

  • Cardiac Complication Risk Profiling for Cancer Survivors via Multi-View Multi-Task Learning
    T. Pham, C. Yin, L. Mehta, X. Zhang and P. Zhang
    In the IEEE International Conference on Data Mining (ICDM), regular paper, 2021.
    pdf
    code

  • Improving Fairness and Privacy in Selection Problems
    M. Khalili, X. Zhang, M. Abroshan and S. Sojoudi
    In the 35th AAAI Conference on Artificial Intelligence (AAAI), 2021.
    pdf

  • Fairness in Learning-Based Sequential Decision Algorithms: A Survey
    X. Zhang and M. Liu
    Springer Studies in Systems, Decision and Control, Handbook on RL and Control.
    pdf

  • Designing Contracts for Trading Private and Heterogeneous Data Using a Biased Differentially Private Algorithm
    M. Khalili*, X. Zhang* and M. Liu
    In IEEE Access, 2021.
    pdf

2020

  • How Do Fair Decisions Fare in Long-term Qualification?
    X. Zhang*, R. Tu*, Y. Liu, M. Liu, H. Kjellström, K. Zhang and C. Zhang
    In the 34th Conference on Neural Information Processing Systems (NeurIPS), 2020.
    pdf
    poster
    slides
    talk
    code

  • Resource Pooling for Shared Fate: Incentivizing Effort in Interdependent Security Games through Cross-investments.
    M. Khalili, X. Zhang and M. Liu
    In IEEE Transactions on Control of Network Systems (TCNS), 2020.
    pdf

  • A Robust Energy and Emissions Conscious Cruise Controller for Connected Vehicles with Privacy Considerations
    C. Huang, X. Zhang, R. Salehi, T. Ersal and A. Stefanopoulou
    In 2020 American Control Conference (ACC), 2020.
    ASME Automotive and Transportation Systems Best Paper Award Finalist
    pdf

2019

  • Group Retention when Using Machine Learning in Sequential Decision Making: the Interplay between User Dynamics and Fairness
    X. Zhang*, M. Khalili*, C. Tekin and M. Liu
    In the 33rd Conference on Neural Information Processing Systems (NeurIPS), 2019.
    Earlier version: in EC Workshop on Mechanism Design for Social Good (MD4SG), 2019.
    pdf
    poster

  • Recycled ADMM: Improving the Privacy and Accuracy of Distributed Algorithms
    X. Zhang, M. Khalili and M. Liu
    In IEEE Transactions on Information Forensics and Security (TIFS), 2019.
    pdf

  • Incentivizing Effort in Interdependent Security Games Using Resource Pooling
    M. Khalili, X. Zhang and M. Liu
    In the 14th Workshop on the Economics of Networks, Systems and Computation (NetEcon), 2019.
    pdf
    slides

  • Effective Premium Discrimination for Designing Cyber Insurance Policies with Rare Losses
    M. Khalili, X. Zhang and M. Liu
    In the 10th Conference on Decision and Game Theory for Security (GameSec), 2019.
    pdf

  • Long-term Impacts of Fair Machine Learning
    X. Zhang, M. Khalili and M. Liu
    In Ergonomics in Design: The Quarterly of Human Factors Applications, 2019.
    pdf

  • Contract Design for Purchasing Private Data Using a Biased Differentially Private Algorithm
    M. Khalili*, X. Zhang* and M. Liu
    In the 14th Workshop on the Economics of Networks, Systems and Computation (NetEcon), 2019.
    pdf
    slides

  • Predictive Cruise Control with Private Vehicle-to-Vehicle Communication for Improving Fuel Consumption and Emissions
    X. Zhang*, C. Huang*, M. Liu, A. Stefanopoulou and T. Ersal
    In IEEE Communications Magazine, 2019.
    pdf

2018

  • Improving the Privacy and Accuracy of ADMM-Based Distributed Algorithms
    X. Zhang, M. Khalili and M. Liu
    In the 35th International Conference on Machine Learning (ICML), 2018.
    pdf
    talk
    poster

  • Recycled ADMM: Improve Privacy and Accuracy with Less Computation in Distributed Algorithms
    X. Zhang, M. Khalili and M. Liu
    In the 56th Annual Allerton Conference on Communication, Control, and Computing (Allerton), 2018.
    pdf
    slides

  • Public Good Provision Games on Networks with Resource Pooling
    M. Khalili, X. Zhang and M. Liu
    In the International Conference on Network Games Control and Optimization (NetGCoop), 2018.
    pdf