Jiaming Xu | Scholars@Duke

Jiaming Xu
Associate Professor of Business Administration

Jiaming Xu is an Associate Professor in the Decision Sciences area. His research focus is on the intersection of computation and statistics. Professor Xu seeks to understand the deep interplay between statistical optimality and computational complexity in high-dimensional statistical inference problems. He has been working on sharp performance analysis of semidefinite programming relaxations and belief propagation for community detection. Professor Xu teaches Decision Analytics and Modeling.

Current Research Interests

Network science, machine learning, high-dimensional statistical inference, information theory, optimization, stochastic systems, game theory, communications and networking

Current Appointments & Affiliations

Associate Professor of Business Administration, Fuqua School of Business, Duke University 2022
Assistant Professor in the Department of Electrical and Computer Engineering, Electrical and Computer Engineering, Pratt School of Engineering 2019
Faculty Network Member of the Duke Institute for Brain Sciences, Duke Institute for Brain Sciences, University Institutes and Centers 2018

Contact Information

Background
Education, Training, & Certifications
- Ph.D., University of Illinois, Urbana-Champaign 2014
- M.S., University of Texas, Austin 2011
- B.S.E., Tsinghua University (China) 2009
Previous Appointments & Affiliations
- Assistant Professor of Business Administration, Fuqua School of Business, Duke University 2018 - 2022
Recognition
In the News
- APR 13, 2022 Fuqua School of Business
  
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Research
Selected Grants
- CAREER: Federated Learning: Statistical Optimality and Provable Security awarded by National Science Foundation 2022 - 2027
- CIF: Medium: Collaborative Research: Learning in Networks: Performance Limits and Algorithms awarded by National Science Foundation 2019 - 2023
- BIGDATA:F: Collaborative Research: Mining for Graphs and High-Dimensional Data: Achieving the Limits awarded by National Science Foundation 2018 - 2021
- CRII: CIF: Learning Hidden Structure in Networks: Fundamental Limits and Efficient Algorithms awarded by National Science Foundation 2018 - 2021
Publications & Artistic Works
Selected Publications
- Academic Articles
  - Wu, Y., J. Xu, and S. H. Yu. “Settling the Sharp Reconstruction Thresholds of Random Graph Matching.” Ieee Transactions on Information Theory 68, no. 8 (August 1, 2022): 5391–5417. https://doi.org/10.1109/TIT.2022.3169005.
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  - Hsu, W. K., J. Xu, X. Lin, and M. R. Bell. “Integrated Online Learning and Adaptive Control in Queueing Systems with Uncertain Payoffs.” Operations Research 70, no. 2 (March 1, 2022): 1166–81. https://doi.org/10.1287/opre.2021.2100.
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  - Fan, Z., C. Mao, Y. Wu, and J. Xu. “Spectral Graph Matching and Regularized Quadratic Relaxations I Algorithm and Gaussian Analysis.” Foundations of Computational Mathematics, January 1, 2022. https://doi.org/10.1007/s10208-022-09570-y.
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  - Fan, Z., C. Mao, Y. Wu, and J. Xu. “Spectral Graph Matching and Regularized Quadratic Relaxations II: Erdős-Rényi Graphs and Universality.” Foundations of Computational Mathematics, January 1, 2022. https://doi.org/10.1007/s10208-022-09575-7.
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  - Moharrami, M., C. Moore, and J. Xu. “The planted matching problem: Phase transitions and exact results.” Annals of Applied Probability 31, no. 6 (December 1, 2021): 2663–2720. https://doi.org/10.1214/20-AAP1660.
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  - Ding, J., Y. Wu, J. Xu, and D. Yang. “Consistent Recovery Threshold of Hidden Nearest Neighbor Graphs.” Ieee Transactions on Information Theory 67, no. 8 (August 1, 2021): 5211–29. https://doi.org/10.1109/TIT.2021.3085773.
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  - Yu, L., J. Xu, and X. Lin. “The Power of D-hops in Matching Power-Law Graphs.” Performance Evaluation Review 49, no. 1 (June 1, 2021): 77–78. https://doi.org/10.1145/3410220.3460098.
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  - Ding, J., Z. Ma, Y. Wu, and J. Xu. “Efficient random graph matching via degree profiles.” Probability Theory and Related Fields 179, no. 1–2 (February 1, 2021): 29–115. https://doi.org/10.1007/s00440-020-00997-4.
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  - Li, X., Y. Chen, and J. Xu. “Convex Relaxation Methods for Community Detection.” Statistical Science 36, no. 1 (February 1, 2021): 2–15. https://doi.org/10.1214/19-STS715.
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  - Yu, L., J. Xu, and X. Lin. “Graph Matching with Partially-Correct Seeds.” Journal of Machine Learning Research 22 (January 1, 2021).
  - Mossel, E., and J. Xu. “Seeded graph matching via large neighborhood statistics.” Random Structures and Algorithms 57, no. 3 (October 1, 2020): 570–611. https://doi.org/10.1002/rsa.20934.
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  - Xu, J., and Y. Zhong. “Improved queue-size scaling for input-queued switches via graph factorization.” Advances in Applied Probability 52, no. 3 (September 1, 2020): 798–824. https://doi.org/10.1017/apr.2020.31.
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  - Bagaria, V., J. Ding, D. Tse, Y. Wu, and J. Xu. “Crosscutting areas hidden Hamiltonian cycle recovery via linear programming.” Operations Research 68, no. 1 (February 1, 2020): 53–70. https://doi.org/10.1287/OPRE.2019.1886.
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  - Chen, Yudong, Lili Su, and Jiaming Xu. “Distributed Statistical Machine Learning in Adversarial Settings.” Acm Sigmetrics Performance Evaluation Review 46, no. 1 (January 17, 2019): 96–96. https://doi.org/10.1145/3308809.3308857.
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  - Su, Lili, and Jiaming Xu. “Securing Distributed Gradient Descent in High Dimensional Statistical Learning.” Proceedings of the Acm on Measurement and Analysis of Computing Systems 3, no. 1 (2019). https://doi.org/10.1145/3311083.
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  - Chen, Yudong, Xiaodong Li, and Jiaming Xu. “Convexified modularity maximization for degree-corrected stochastic block models.” The Annals of Statistics 46, no. 4 (August 1, 2018). https://doi.org/10.1214/17-aos1595.
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  - Xu, Jiaming, Bruce Hajek, and Yihong Wu. “Recovering a hidden community beyond the Kesten-Stigum threshold in O(|E|log*|V) time.” Journal of Applied Probability 55, no. 2 (July 15, 2018): 325–52.
  - Banks, Jess, Cristopher Moore, Roman Vershynin, Nicolas Verzelen, and Jiaming Xu. “Information-Theoretic Bounds and Phase Transitions in Clustering, Sparse PCA, and Submatrix Localization.” Ieee Transactions on Information Theory 64, no. 7 (July 2018): 4872–94. https://doi.org/10.1109/tit.2018.2810020.
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  - Xu, Jiaming, Bruce Hajek, and Yihong Wu. “Submatrix localization via message passing.” Journal of Machine Learning Research 18, no. 186 (April 15, 2018): 1–52.
  - Hajek, Bruce, Yihong Wu, and Jiaming Xu. “Information Limits for Recovering a Hidden Community.” Ieee Transactions on Information Theory 63, no. 8 (August 2017): 4729–45. https://doi.org/10.1109/tit.2017.2653804.
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  - Hajek, Bruce, Yihong Wu, and Jiaming Xu. “Achieving Exact Cluster Recovery Threshold via Semidefinite Programming: Extensions.” Ieee Transactions on Information Theory 62, no. 10 (October 2016): 5918–37. https://doi.org/10.1109/tit.2016.2594812.
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  - Hajek, Bruce, Yihong Wu, and Jiaming Xu. “Achieving Exact Cluster Recovery Threshold via Semidefinite Programming.” Ieee Transactions on Information Theory 62, no. 5 (May 2016): 2788–97. https://doi.org/10.1109/tit.2016.2546280.
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  - Xu, J., M. Lelarge, and L. Massoulié. “Reconstruction in the labeled stochastic block model.” Ieee Transactions on Network Science and Engineering 2, no. 4 (October 2015): 152–63.
  - Xu, J., and Y. Chen. “Statistical-computational tradeoffs in planted problems and submatrix localization with a growing number of clusters and submatrices.” Journal of Machine Learning Research 17, no. 1 (February 2014): 882–938.
  - Xu, Jiaming, and Bruce Hajek. “The Supermarket Game.” Stochastic Systems 3, no. 2 (December 2013): 405–41. https://doi.org/10.1287/12-ssy093.
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  - Xu, J., J. Andrews, and S. Jafar. “MISO broadcast channels with delayed finite-rate feedback: Predict or observe?” Ieee Transactions on Wireless Communications 11, no. 4 (April 2012): 1456–67.
  - Xu, Jiaming, Jun Zhang, and Jeffrey G. Andrews. “On the Accuracy of the Wyner Model in Cellular Networks.” Ieee Transactions on Wireless Communications 10, no. 9 (September 2011): 3098–3109. https://doi.org/10.1109/twc.2011.062911.100481.
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- Conference Papers
  - Xu, J., K. Xu, and D. Yang. “Learner-Private Convex Optimization.” In Ieee Transactions on Information Theory, 69:528–47, 2023. https://doi.org/10.1109/TIT.2022.3203989.
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- Preprints
  - Mao, Cheng, Yihong Wu, Jiaming Xu, and Sophie H. Yu. “Random graph matching at Otter's threshold via counting chandeliers,” September 25, 2022.
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  - Yu, Liren, Jiaming Xu, and Xiaojun Lin. “SeedGNN: Graph Neural Networks for Supervised Seeded Graph Matching,” May 26, 2022.
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  - Wang, Haoyu, Yihong Wu, Jiaming Xu, and Israel Yolou. “Random Graph Matching in Geometric Models: the Case of Complete Graphs,” February 21, 2022.
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  - Mao, Cheng, Yihong Wu, Jiaming Xu, and Sophie H. Yu. “Testing network correlation efficiently via counting trees,” October 22, 2021.
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  - Su, Lili, Jiaming Xu, and Pengkun Yang. “A Non-parametric View of FedAvg and FedProx: Beyond Stationary Points,” June 29, 2021.
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  - Ding, Jian, Yihong Wu, Jiaming Xu, and Dana Yang. “The planted matching problem: Sharp threshold and infinite-order phase transition,” March 16, 2021.
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  - Xu, Jiaming, Kuang Xu, and Dana Yang. “Learner-Private Convex Optimization,” February 23, 2021.
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  - Yu, Liren, Jiaming Xu, and Xiaojun Lin. “The Power of $D$-hops in Matching Power-Law Graphs,” February 23, 2021.
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  - Wu, Yihong, Jiaming Xu, and Sophie H. Yu. “Settling the Sharp Reconstruction Thresholds of Random Graph Matching,” January 29, 2021.
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  - Wu, Yihong, Jiaming Xu, and Sophie H. Yu. “Testing correlation of unlabeled random graphs,” August 23, 2020.
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  - Yu, Liren, Jiaming Xu, and Xiaojun Lin. “Graph Matching with Partially-Correct Seeds,” April 8, 2020.
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  - Moharrami, Mehrdad, Cristopher Moore, and Jiaming Xu. “The Planted Matching Problem: Phase Transitions and Exact Results,” December 18, 2019.
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  - Ding, Jian, Yihong Wu, Jiaming Xu, and Dana Yang. “Consistent recovery threshold of hidden nearest neighbor graphs,” November 18, 2019.
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  - Xu, Jiaming, Kuang Xu, and Dana Yang. “Optimal query complexity for private sequential learning against eavesdropping,” September 21, 2019.
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  - Fan, Zhou, Cheng Mao, Yihong Wu, and Jiaming Xu. “Spectral Graph Matching and Regularized Quadratic Relaxations II: Erdős-Rényi Graphs and Universality,” July 20, 2019.
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  - Fan, Zhou, Cheng Mao, Yihong Wu, and Jiaming Xu. “Spectral Graph Matching and Regularized Quadratic Relaxations I: The Gaussian Model,” July 20, 2019.
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  - Reeves, Galen, Jiaming Xu, and Ilias Zadik. “The All-or-Nothing Phenomenon in Sparse Linear Regression,” March 12, 2019.
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  - Xu, Jiaming, and Yuan Zhong. “Improved queue-size scaling for input-queued switches via graph factorization,” March 1, 2019.
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  - Ding, Jian, Zongming Ma, Yihong Wu, and Jiaming Xu. “Efficient random graph matching via degree profiles,” November 19, 2018.
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  - Li, Xiaodong, Yudong Chen, and Jiaming Xu. “Convex Relaxation Methods for Community Detection,” September 30, 2018.
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  - Mossel, Elchanan, and Jiaming Xu. “Seeded Graph Matching via Large Neighborhood Statistics,” July 26, 2018.
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  - Wu, Yihong, and Jiaming Xu. “Statistical Problems with Planted Structures: Information-Theoretical and Computational Limits,” May 31, 2018.
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  - Su, Lili, and Jiaming Xu. “Securing Distributed Gradient Descent in High Dimensional Statistical Learning,” April 26, 2018.
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  - Bagaria, Vivek, Jian Ding, David Tse, Yihong Wu, and Jiaming Xu. “Hidden Hamiltonian Cycle Recovery via Linear Programming,” April 15, 2018.
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  - Xu, Jiaming. “Rates of Convergence of Spectral Methods for Graphon Estimation,” September 10, 2017.
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  - Banks, Jess, Cristopher Moore, Nicolas Verzelen, Roman Vershynin, and Jiaming Xu. “Information-theoretic bounds and phase transitions in clustering, sparse PCA, and submatrix localization,” July 18, 2016.
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  - Krzakala, Florent, Jiaming Xu, and Lenka Zdeborová. “Mutual Information in Rank-One Matrix Estimation,” March 28, 2016.
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  - Hajek, Bruce, Yihong Wu, and Jiaming Xu. “Semidefinite Programs for Exact Recovery of a Hidden Community,” February 20, 2016.
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  - Chen, Yudong, Xiaodong Li, and Jiaming Xu. “Convexified Modularity Maximization for Degree-corrected Stochastic Block Models,” December 28, 2015.
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  - Hajek, Bruce, Yihong Wu, and Jiaming Xu. “Submatrix localization via message passing,” October 30, 2015.
    Link to Item
  - Hajek, Bruce, Yihong Wu, and Jiaming Xu. “Recovering a Hidden Community Beyond the Kesten-Stigum Threshold in $O(|E| \log^*|V|)$ Time,” October 9, 2015.
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  - Hajek, Bruce, Yihong Wu, and Jiaming Xu. “Information Limits for Recovering a Hidden Community,” September 25, 2015.
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  - Mossel, Elchanan, and Jiaming Xu. “Density Evolution in the Degree-correlated Stochastic Block Model,” September 10, 2015.
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  - Mossel, Elchanan, and Jiaming Xu. “Local Algorithms for Block Models with Side Information,” August 10, 2015.
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  - Hajek, Bruce, Yihong Wu, and Jiaming Xu. “Achieving Exact Cluster Recovery Threshold via Semidefinite Programming: Extensions,” February 26, 2015.
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  - Wu, Rui, Jiaming Xu, R. Srikant, Laurent Massoulié, Marc Lelarge, and Bruce Hajek. “Clustering and Inference From Pairwise Comparisons,” February 16, 2015.
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  - Lelarge, Marc, Laurent Massoulié, and Jiaming Xu. “Reconstruction in the Labeled Stochastic Block Model,” February 11, 2015.
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  - Hajek, Bruce, Yihong Wu, and Jiaming Xu. “Achieving Exact Cluster Recovery Threshold via Semidefinite Programming,” November 24, 2014.
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  - Xu, Jiaming, Laurent Massoulié, and Marc Lelarge. “Edge Label Inference in Generalized Stochastic Block Models: from Spectral Theory to Impossibility Results,” June 26, 2014.
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  - Hajek, Bruce, Yihong Wu, and Jiaming Xu. “Computational Lower Bounds for Community Detection on Random Graphs,” June 25, 2014.
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  - Hajek, Bruce, Sewoong Oh, and Jiaming Xu. “Minimax-optimal Inference from Partial Rankings,” June 21, 2014.
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  - Chen, Yudong, and Jiaming Xu. “Statistical-Computational Tradeoffs in Planted Problems and Submatrix Localization with a Growing Number of Clusters and Submatrices,” February 6, 2014.
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  - Xu, Jiaming, Rui Wu, Kai Zhu, Bruce Hajek, R. Srikant, and Lei Ying. “Jointly Clustering Rows and Columns of Binary Matrices: Algorithms and Trade-offs,” October 1, 2013.
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  - Xu, Jiaming, and Bruce Hajek. “The Supermarket Game,” February 9, 2012.
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  - Xu, Jiaming, Jeffrey G. Andrews, and Syed A. Jafar. “Broadcast Channels with Delayed Finite-Rate Feedback: Predict or Observe?,” May 18, 2011.
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  - Xu, Jiaming, Jun Zhang, and Jeffery G. Andrews. “On the Accuracy of the Wyner Model in Cellular Networks,” September 29, 2010.
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Teaching & Mentoring
Recent Courses
Scholarly, Clinical, & Service Activities
Outreach & Engaged Scholarship
- Data+ Project Leader. Data+. 2021 - 2022 2021 - 2022

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Education, Training, & Certifications

Previous Appointments & Affiliations

In the News

Selected Grants

Selected Publications

Academic Articles

Conference Papers

Preprints

Recent Courses

Outreach & Engaged Scholarship