Publications

Weidong Liu, Xiaojun Mao, Xiaofei Zhang, Xin Zhang (2024). Robust Personalized Federated Learning with Sparse Penalization. Journal of the American Statistical Association (2024).

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Weidong Liu, Xiaojun Mao, Xiaofei Zhang, Xin Zhang (2024). Efficient Sparse Least Absolute Deviation Regression with Differential Privacy. IEEE Transactions on Information Forensics and Security (2024).

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Zhuqing Liu, Xin Zhang, Songtao Lu, Jia Liu (2023). PRECISION: Decentralized Constrained Min-Max Learning with Low Communication and Sample Complexities. In ACM Mobihoc 2023.

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Zhuqing Liu, Xin Zhang, Prashant Khanduri, Songtao Lu, Jia Liu (2023). Prometheus: Taming Sample and Communication Complexities in Constrained Decentralized Stochastic Bilevel Learning. In ICML 2023.

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Qinglong Tian, Xin Zhang, Jiwei Zhao (2023). ELSA: Efficient Label Shift Adaptation through the Lens of Semiparametric Models. In ICML 2022.

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Xin Wang, Xin Zhang, Zhengyuan Zhu (2023). Clustered coefficient regression models for Poisson process with an application to seasonal warranty claim data. Technometrics (2023):1-18.

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Xin Zhang, Jia Liu, Zhengyuan Zhu (2022). Learning Coefficient Heterogeneity over Networks: A Distributed Spanning-Tree-Based Fused-Lasso Regression. Journal of the American Statistical Association (2022):1-13.

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Zhuqing Liu, Xin Zhang, Jia Liu (2022). SYNTHESIS: A semi-asynchronous path-integrated stochastic gradient method for distributed learning in computing clusters. In ACM Mobihoc 2022.

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Xin Zhang, Minghong Fang, Zhuqing Liu, Haibo Yang, Jia Liu, Zhengyuan Zhu (2022). NET-FLEET: Achieving linear convergence speedup for fully decentralized federated learning with heterogeneous data. In ACM Mobihoc 2022.

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Zhuqing Liu, Xin Zhang, Prashant Khanduri, Songtao Lu, Jia Liu (2022). INTERACT: Achieving Low Sample and Communication Complexities in Decentralized Bilevel Learning over Networks. In ACM Mobihoc 2022.

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Haibo Yang, Zhuqing Liu, Xin Zhang, Jia Liu (2022). SAGDA: Achieving O(ε−2) Communication Complexity in Federated Min-Max Learning. In Neurips 2022.

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Haibo Yang, Xin Zhang, Prashant Khanduri, Jia Liu (2022). Anarchic federated learning. In ICML (2022).

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Weidong Liu, Xiaojun Mao, Xin Zhang (2022). Fast and Robust Sparsity Learning over Networks: A Decentralized Surrogate Median Regression Approach. IEEE Transactions on Signal Processing 70 (2022).

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Xin Zhang, Zhuqing Liu, Jia Liu, Zhengyuan Zhu, Songtao Lu (2021). Taming Communication and Sample Complexities in Decentralized Policy Evaluation for Cooperative Multi-Agent Reinforcement Learning. In Neurips 2021.

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Xin Zhang, Jia Liu, Zhengyuan Zhu, Elizabeth Serena Bentley (2021). GT-STORM: Taming sample, communication, and memory complexities in decentralized non-convex learning. In ACM Mobihoc 2021.

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Xin Zhang, Jia Liu, Zhengyuan Zhu, Elizabeth Serena Bentley (2021). Low Sample and Communication Complexities in Decentralized Learning: A Triple Hybrid Approach. In IEEE INFOCOM 2021.

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Xin Zhang, Jia Liu, Zhengyuan Zhu (2020). Taming Convergence for Asynchronous Stochastic Gradient Descent with Unbounded Delay in Non-Convex Learning. In IEEE CDC 2020.

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Xin Zhang, Minghong Fang, Jia Liu, Zhengyuan Zhu (2020). Private and communication-efficient edge learning: a sparse differential gaussian-masking distributed SGD approach. In ACM Mobihoc 2020.

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Haibo Yang, Xin Zhang, Minghong Fang, Jia Liu (2020). Adaptive multi-hierarchical signSGD for communication-efficient distributed optimization. In SPAWC 2020.

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Haibo Yang, Xin Zhang, Minghong Fang, Jia Liu (2019). Byzantine-resilient stochastic gradient descent for distributed learning: A lipschitz-inspired coordinate-wise median approach. In IEEE CDC 2019.

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Xin Zhang, Jia Liu, Zhengyuan Zhu, Elizabeth S. Bentley (2019). Compressed distributed gradient descent: Communication-efficient consensus over networks. In IEEE INFOCOM 2019.

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Xin Zhang, Zhengyuan Zhu (2019). Spatial CUSUM for Signal Region Detection.

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Xin Zhang, Limin Li, Michael K.Ng, Shuqin Zhang (2017). Drug–target interaction prediction by integrating multiview network data. Computational biology and chemistry, 69, pp.185-193.

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Xin Zhang, Weiguo Gao, Yun Su (2015). Electricity consumer archetypes study based on functional data analysis and K-means algorithm. Power system technology, 39 (2).

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Xin Zhang (2015). An example preprint / working paper.

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