Jiaming Xu

Jiaming Xu

Assistant Professor of Business Administration

Overview

Jiaming Xu is an Assistant 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.

Education & Training

  • Ph.D., University of Illinois, Urbana-Champaign 2014

  • M.S., University of Texas, Austin 2011

  • B.S.E., Tsinghua University (China) 2009

Selected Grants

CIF: Medium: Collaborative Research: Learning in Networks: Performance Limits and Algorithms awarded by National Science Foundation (Principal Investigator). 2019 to 2023

BIGDATA:F: Collaborative Research: Mining for Graphs and High-Dimensional Data: Achieving the Limits awarded by National Science Foundation (Principal Investigator). 2018 to 2021

CRII: CIF: Learning Hidden Structure in Networks: Fundamental Limits and Efficient Algorithms awarded by National Science Foundation (Principal Investigator). 2018 to 2021

Chen, Yudong, et al. “Convexified modularity maximization for degree-corrected stochastic block models.” The Annals of Statistics, vol. 46, no. 4, Institute of Mathematical Statistics, Aug. 2018, pp. 1573–602. Crossref, doi:10.1214/17-aos1595. Full Text

Xu, Jiaming, et al. “Recovering a hidden community beyond the Kesten-Stigum threshold in O(|E|log*|V) time.” Journal of Applied Probability, vol. 55, no. 2, Applied Probability Trust, July 2018, pp. 325–52.

Banks, Jess, et al. “Information-Theoretic Bounds and Phase Transitions in Clustering, Sparse PCA, and Submatrix Localization.” Ieee Transactions on Information Theory, vol. 64, no. 7, Institute of Electrical and Electronics Engineers (IEEE), July 2018, pp. 4872–94. Crossref, doi:10.1109/tit.2018.2810020. Full Text

Xu, Jiaming, et al. “Submatrix localization via message passing.” Journal of Machine Learning Research, vol. 18, no. 186, Microtome Publishing, Apr. 2018, pp. 1–52.

Hajek, Bruce, et al. “Information Limits for Recovering a Hidden Community.” Ieee Transactions on Information Theory, vol. 63, no. 8, Institute of Electrical and Electronics Engineers (IEEE), Aug. 2017, pp. 4729–45. Crossref, doi:10.1109/tit.2017.2653804. Full Text

Hajek, Bruce, et al. “Achieving Exact Cluster Recovery Threshold via Semidefinite Programming: Extensions.” Ieee Transactions on Information Theory, vol. 62, no. 10, Institute of Electrical and Electronics Engineers (IEEE), Oct. 2016, pp. 5918–37. Crossref, doi:10.1109/tit.2016.2594812. Full Text

Hajek, Bruce, et al. “Achieving Exact Cluster Recovery Threshold via Semidefinite Programming.” Ieee Transactions on Information Theory, vol. 62, no. 5, Institute of Electrical and Electronics Engineers (IEEE), May 2016, pp. 2788–97. Crossref, doi:10.1109/tit.2016.2546280. Full Text

Lelarge, Marc, et al. “Reconstruction in the Labelled Stochastic Block Model.” Ieee Transactions on Network Science and Engineering, vol. 2, no. 4, Institute of Electrical and Electronics Engineers (IEEE), Oct. 2015, pp. 152–63. Crossref, doi:10.1109/tnse.2015.2490580. Full Text

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, vol. 17, no. 1, Microtome Publishing, Feb. 2014, pp. 882–938.

Xu, Jiaming, and Bruce Hajek. “The Supermarket Game.” Stochastic Systems, vol. 3, no. 2, Institute for Operations Research and the Management Sciences (INFORMS), Dec. 2013, pp. 405–41. Crossref, doi:10.1287/12-ssy093. Full Text

Pages