Long Nguyen

Assistant Professor, Department of Statistics,
Dept of Electrical Engineering and Computer Science (by courtesy),
University of Michigan

Email: xuanlong@umich.edu
Office: 456 West Hall, Phone: 734-763-3499, Fax: 734-763-4676

Mail Address: 439 West Hall, 1085 South University, Ann Arbor, MI 48109-1107

[Research] [Teaching] [Students] [Publications] [Biography]

Research interests

Nonparametric Bayesian statistics
Variational and decentralized statistical inference
Machine learning in networks and distributed systems
Analysis of signals, texts, images and other spatio-temporal and functional data

A biased sample of papers

Identifiability and optimal rates of convergence for parameters of multiple types in finite mixtures. N. Ho and X. Nguyen. Technical Report No. 536, Dept of Statistics, Univ of Michigan, January 2015.
- The results of Section 3 of this long technical report were submitted to a journal: On strong identifiability and optimal rates of parameter estimation in finite mixtures.
- Parts of Section 4 were submitted to another journal: Optimal rates of parameter estimation for some weakly identifiable finite mixtures.
Borrowing strength in hierarchical Bayes: convergence of the Dirichlet base measure. X. Nguyen. To appear, Bernoulli, 2015. [Originally listed as Technical Report No. 532, Dept of Statistics, Univ of Michigan, January 2013.]
Posterior contraction of the population polytope in finite admixture models. X. Nguyen. In press, Bernoulli.
Parallel feature selection inspired by group testing. Y. Zhou, C. Zhang, U. Porwal, H. Q. Ngo, X. Nguyen, C. Ré, and V. Govindaraju. Advances in Neural Information Processing Systems (NIPS) 27, 2014.
Bayesian nonparametric multilevel clustering with group-level contexts. V. Nguyen, D. Phung, X. Nguyen, S. Venkatesh and H. H. Bui. Proceedings of the ICML, 2014.
Bayesian nonparametric modeling for functional analysis of variance. X. Nguyen and A. E. Gelfand. Annals of the Institute of Statistical Mathematics, 66(3), 496--526, 2014. DOI:10.1007/s10463-013-0436-7.
Bayesian inference as iterated random functions with applications to sequential inference in graphical models. A. A. Amini and X. Nguyen. Advances in Neural Information Processing Systems (NIPS) 26, 2013.
Convergence of latent mixing measures in finite and infinite mixture models . X. Nguyen. Annals of Statistics, 41(1), 370--400, 2013. [Corrections]
Sequential detection of multiple change points in networks: A graphical model approach. A. A. Amini and X. Nguyen. IEEE Transactions on Information Theory, 59(9), 5824--5841, 2013.
The Dirichlet labeling process for clustering functional data. X. Nguyen and A. E. Gelfand. Statistica Sinica 21(3), 1249--1289, 2011.
Inference of global clusters from locally distributed data. X. Nguyen. Bayesian Analysis, 5(4), 817--846, 2010.
Estimating divergence functionals and the likelihood ratio by convex risk minimization. X. Nguyen, M. J. Wainwright and M. I. Jordan. IEEE Transactions on Information Theory, 56(11), 5847--5861, 2010.
On surrogate loss functions and f-divergences. X. Nguyen, M. J. Wainwright and M.I. Jordan. Annals of Statistics, 37(2), 876--904, 2009.
More ...

Selected talk slides

Borrowing strength in hierarchical Bayes: convergence of the Dirichlet base measure. Bayesian Nonparametrics conference, Amsterdam, June 2013.
Convergence of latent mixing measures in finite and infinite mixture models. Bayesian Nonparametrics Workshop at ICERM, Providence, September 2012.
Clustering problems, mixture models and Bayesian nonparametrics. VIASM Summer School, Hanoi, July 2012. [Slides 1 ] [Notes 2 ]
Message-passing sequential detection of multiple change points in networks. IEEE Symposium on Information Theory, Boston, July 2012.
Inference of functional clusters from non-functional data . Midwest Statistics Research Colloquium, Madison, March 2012.
Dirichlet labeling and hierarchical processes for clustering functional data . IMS-China Conference, Xi'an, July 2011.
Decentralized decision making with spatially distributed data . AI Seminar, University of Michigan, Oct 2009.
Surrogate loss functions, divergences and decentralized detection. Thesis talk, UC Berkeley, May 2007.
Anomaly and sequential detection with time series data . Tutorial lectures given at Berkeley, 2006.

Biographical information

Ph.D, UC Berkeley, 2007 (advised by Michael I Jordan and Martin Wainwright)
Postdoctoral fellow, Duke University and SAMSI, 2007--2009 (mentored by Alan Gelfand)
Best Paper Award, 21st International Conference on Machine Learning, 2004
Young Author's Best Paper Award by the IEEE Signal Processing Society, 2007
Leon O. Chua Award for outstanding achievement in an area of nonlinear science, UC Berkeley, 2007
CAREER Award, National Science Foundation, Division of Mathematical Sciences, 2014--2019
Best Paper Award, 31st International Conference on Machine Learning, 2014
Associate Editor, Bayesian Analysis
Area Chair, AISTATS (2015), ICML (2015)

Students

Nhat Ho
Hossein Keshavarz (joint with Clay Scott)
Mikhail Yurochkin

Former students, postdocs and visitors

Zhaoshi Meng (PhD 2014, joint with Al Hero; Senior Researcher, Vicarious, CA)
Arash Ali Amini (Postdoctoral fellow 2011--2014; Assistant Professor, UCLA)
Vijay Manikandan Janakiraman (PhD 2013, joint with Dennis Assanis; Research Scientist, NASA's Ames Research)
Jian Tang (Visiting PhD student from Peking University 2012--2013; Researcher, Microsoft Research Asia, Beijing)
Kohinoor Dasgupta (PhD 2012, joint with Vijay Nair and Stilian Stoev; Senior Biostatistician, Novartis India)
Cen Guo (PhD 2012, joint with Tailen Hsing; Senior Analyst, United Airlines, Chicago)
Bopeng Li (MS 2012; in Statistics PhD program, University of Michigan)
Hyun-Chul Kim (Visiting Scholar 2010--2011; Research Professor, Yonsei University, Seoul)