Long Nguyen's papers listed by topics

1. Graphical and nonparametric Bayesian modeling
2. Nonparametric estimation
3. Learning in networks and systems
4. Kernel and Gaussian process methods
5. Combinatorial Search and CSP
6. Theses

Graphical, hierarchical and nonparametric Bayesian modeling

• Borrowing strength in hierarchical Bayes: convergence of the Dirichlet base measure. X. Nguyen. Technical Report No. 532, Department of Statistics, University of Michigan, January 2013.

• Posterior contraction of the population polytope in finite admixture models. X. Nguyen. Technical Report No. 528, Department of Statistics, University of Michigan, May 2012.

• Convergence of latent mixing measures in finite and infinite mixture models . X. Nguyen. Annals of Statistics, 41(1), 370--400, 2013. [arXiv:1109.3250 ]

• Sequential detection of multiple change points in networks: A graphical model approach. A. Amini and X. Nguyen. IEEE Transactions on Information Theory, to appear (2013).

• Message-passing sequential detection of multiple change points in networks. X. Nguyen, A. Amini and R. Rajagopal. IEEE International Symposium on Information Theory (ISIT), Boston, July 2012.

• The Dirichlet labeling process for clustering functional data. X. Nguyen and A. E. Gelfand. Statistica Sinica 21(3), 1249-1289, 2011.

• Inferential ecosystem models, from network data to prediction. J.S. Clark, P. Agarwal, D.M. Bell, P. Flikkema, A. Gelfand, X. Nguyen, E. Ward, and J. Yang. Ecological Applications, 21(5), 1523–1536, 2011.

• Inference of global clusters from locally distributed data. X. Nguyen. Bayesian Analysis, 5(4), 817--846, 2010.
  • Preliminary version appeared as Graphically dependent and spatially varying Dirichlet process mixtures. X. Nguyen. Technical Report 504, Dept. of Statistics, University of Michigan, January 2010. [ arXiv link ].

• Bayesian nonparametric modeling for functional analysis of variance. X. Nguyen and A. E. Gelfand. Technical Report No. 515, Department of Statistics, University of Michigan, Nov 2010.

• On the concentration of expectation and approximate inference in layered networks. X. Nguyen and M. I. Jordan. Advances in Neural Information Processing Systems 16 (NIPS), 2003. [ citations ]
  • Full-length version [ ps ].

Nonparametric Estimation

• Borrowing strength in hierarchical Bayes: convergence of the Dirichlet base measure. X. Nguyen. Technical Report No. 532, Department of Statistics, University of Michigan, January 2013.

• Convergence of latent mixing measures in finite and infinite mixture models . X. Nguyen. Annals of Statistics, 41(1), 370--400, 2013. [arXiv:1109.3250 ]

• 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. [ arXiv link ].

• On surrogate loss functions and f-divergences. X. Nguyen, M.J. Wainwright and M.I. Jordan. Annals of Statistics, (37)2, 876--904, 2009.

• Support vector machines, data reduction and approximate kernel matrices. X. Nguyen, L. Huang and A. Joseph. Proceedings of European Conference on Machine Learning (ECML), Belgium, September, 2008. (Previously listed as SAMSI Technical report No. 2008-3, April 2008.)

• Estimating divergence functionals and the likelihood ratio by penalized convex risk minimization. X. Nguyen, M. J. Wainwright and M. I. Jordan. Advances in Neural Information Processing Systems 20 (NIPS), 2007 [ Typo ] [ Full version ]

• Nonparametric estimation of the likelihood ratio and divergence functionals. X. Nguyen, M. J. Wainwright and M. I. Jordan. IEEE International Symposium on Information Theory (ISIT), Nice, France, July 2007. [ Full version ]

• Nonparametric decentralized detection using kernel methods. X. Nguyen, M. J. Wainwright and M. I. Jordan. IEEE Transactions on Signal Processing, 53(11), 4053--4066, 2005. "2007 IEEE Signal Processing Society's Young Author Best paper award".

Learning in networks and systems

• A Lyapunov based stable online learning algorithm for nonlinear dynamical systems using extreme learning machines. V. M. Janakiraman, X. Nguyen, and D. Assanis. To appear, Proceedings of the International Joint Conference on Neural Networks (IJCNN) , Dallas, August 2013.

• Sequential detection of multiple change points in networks: A graphical model approach. A. Amini and X. Nguyen. IEEE Transactions on Information Theory, to appear (2013).

• Message-passing sequential detection of multiple change points in networks. X. Nguyen, A. Amini and R. Rajagopal. IEEE International Symposium on Information Theory (ISIT), Boston, July 2012.

• Nonlinear identification of a gasoline HCCI engine using neural networks coupled with principal component analysis. V. M. Janakiraman, X. Nguyen and D. Assanis. Journal of Applied Soft Computing, 13(5), 2375--2389, 2013.

• Wireless sensor networks: Statistical issues and challenges. S. N. Lahiri, X. Nguyen, J. Yang, Z. Zhu, and P. Banerjee. Journal of the Indian Statistical Association, 50(1-2), 151--191, 2012.

• Inferential ecosystem models, from network data to prediction. J. S. Clark, P. Agarwal, D. M. Bell, P. Flikkema, A. Gelfand, X. Nguyen, E. Ward, and J. Yang. Ecological Applications, 21(5), 1523–1536, 2011.

• Simultaneous sequential detection of multiple interacting faults. R. Rajagopal, X. Nguyen, S.C. Ergen and P. Varaiya. http://arxiv.org/abs/1012.1258

• Localization problem in sensor networks: The machine learning approach. Duc A. Tran, X. Nguyen, and T. Nguyen. Book chapter in G. Mao and B. Fidan (Eds), Localization Algorithms and Strategies for Wireless Sensor Networks: Monitoring and Surveillance Techniques for Target Tracking, IGI Global Publisher, 2009.

• Distributed online simultaneous fault detection for multiple sensors. R. Rajagopal, X. Nguyen, S. Ergen and P. Varaiya. Proceedings of the 7th International Conference on Information Processing in Sensor Networks (IPSN) , St. Louis, MO, April, 2008.

• On optimal quantization rules in some problems in sequential decentralized detection. X. Nguyen, M. J. Wainwright and M. I. Jordan. IEEE Transactions on Information Theory, 54(7), 3285--3295, 2008.
  • Technical report version (outdated): On optimal quantization rules in some sequential decision problems. X. Nguyen, M. J. Wainwright and M. I. Jordan. Technical Report 708, Department of Statistics, UC Berkeley, June 2006.
  • Conference version: On optimal quantization rules in sequential decision problems. X. Nguyen, M. J. Wainwright and M. I. Jordan. IEEE International Symposium on Information Theory (ISIT), Seattle, CA 2006.

• Communication-Efficient Online Detection of Network-Wide Anomalies. L. Huang, X. Nguyen, M. Garofalakis, J. Hellerstein, A. Joseph, M.I. Jordan and N. Taft. 26th Annual IEEE INFOCOM, Anchorage, Alaska, May 2007.

• In-network PCA and anomaly detection. L. Huang, X. Nguyen, M. Garofalakis, M. I. Jordan, A. D. Joseph and N. Taft. Advances in Neural Information Processing Systems 19 (NIPS), 2006.
  • Tech report version: In-network PCA and network anomaly detection, Technical Report UCB/EECS-2006-99, Department of EECS, UC Berkeley, July 2006. [ pdf ]

• On divergences, surrogate loss functions and decentralized detection. X. Nguyen, M. J. Wainwright and M. I. Jordan. Technical Report 695, Department of Statistics, UC Berkeley, October 2005. (An abridged version appears in Annals of Statistics, 2009).
  Conference versions:
  • Divergences, surrogate loss functions and experimental design. X. Nguyen, M. J. Wainwright and M. I. Jordan. Advances in Neural Information Processing Systems 18 (NIPS), 2005. [ pdf ]
  • On information divergence measures, surrogate loss functions and decentralized hypothesis testing. X. Nguyen, M. J. Wainwright and M. I. Jordan. 43rd Annual Allerton Conference on Communication, Control and Computing, Allerton, IL, September 2005. [ pdf ]

• A kernel-based learning approach to ad hoc sensor network localization. X. Nguyen, M. I. Jordan and B. Sinopoli. ACM Transactions on Sensor Networks, 1, 134--152, 2005. Also listed as technical report CSD-04-1319, Computer Science Division, University of California, Berkeley, April 2004. [ Addendum].
  • Conference version: A kernel-based learning approach to ad hoc sensor network localization. X. Nguyen, M. I. Jordan and B. Sinopoli. In Proc. AAAI-2004 Workshop on Sensor Networks , San Jose, CA, July 2004.

• Nonparametric decentralized detection using kernel methods. X. Nguyen, M. J. Wainwright and M. I. Jordan. IEEE Transactions on Signal Processing, 53(11), 4053--4066, 2005. "2007 IEEE Signal Processing Society's Young Author Best paper award".
  • Conference version: Decentralized detection and classification using kernel methods. X. Nguyen, M. J. Wainwright and M. I. Jordan. In Proceedings of the 21st International Conference on Machine Learning (ICML), Banff, Canada, 2004. "Outstanding Student Paper Award".
  • Tech report version: Decentralized Detection and Classification using Kernel Methods. X. Nguyen, M. J. Wainwright and M. I. Jordan. Technical Report 658, Department of Statistics, University of California, Berkeley, April 2004. [ pdf ].

• A new localization algorithm for sensor networks using RF signal strength. X. Nguyen and T. Rattentbury, CS 252 report, Spring 2003.

Reproducing kernel Hilbert space and Gaussian Process Methods

• The Dirichlet labeling process for clustering functional data. X. Nguyen and A. E. Gelfand. Statistica Sinica 21(3), 1249-1289, 2011.

• 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. [ arXiv link ].

• Bayesian nonparametric modeling for functional analysis of variance. X. Nguyen and A. E. Gelfand. Technical Report No. 515, Department of Statistics, University of Michigan, Nov 2010.

• Inference of global clusters from locally distributed data. X. Nguyen. Bayesian Analysis, 5(4), 817--846, 2010.
  • Preliminary version appeared as Graphically dependent and spatially varying Dirichlet process mixtures. X. Nguyen. Technical Report 504, Dept. of Statistics, University of Michigan, January 2010. [ arXiv link ].

• Support vector machines, data reduction and approximate kernel matrices. X. Nguyen, L. Huang and A. Joseph. Proceedings of European Conference on Machine Learning (ECML), Belgium, September, 2008. (Previously listed as SAMSI Technical report No. 2008-3, April 2008.)

• Estimating divergence functionals and the likelihood ratio by penalized convex risk minimization. X. Nguyen, M. J. Wainwright and M. I. Jordan. Advances in Neural Information Processing Systems 20 (NIPS), 2007 [ Typo ] [ Full version ]

• Nonparametric estimation of the likelihood ratio and divergence functionals. X. Nguyen, M. J. Wainwright and M. I. Jordan. IEEE International Symposium on Information Theory (ISIT), Nice, France, July 2007. [ Full version ]

• A kernel-based learning approach to ad hoc sensor network localization. X. Nguyen, M. I. Jordan and B. Sinopoli. ACM Transactions on Sensor Networks, 1, 134--152, 2005. Also listed as technical report CSD-04-1319, Computer Science Division, University of California, Berkeley, April 2004. [ Addendum].
  • Conference version: A kernel-based learning approach to ad hoc sensor network localization. X. Nguyen, M. I. Jordan and B. Sinopoli. In Proc. AAAI-2004 Workshop on Sensor Networks , San Jose, CA, July 2004.

• Nonparametric decentralized detection using kernel methods. X. Nguyen, M. J. Wainwright and M. I. Jordan. IEEE Transactions on Signal Processing, 53(11), 4053--4066, 2005. "2007 IEEE Signal Processing Society's Young Author Best paper award".
  • Conference version: Decentralized detection and classification using kernel methods. X. Nguyen, M. J. Wainwright and M. I. Jordan. In Proceedings of the 21st International Conference on Machine Learning (ICML), Banff, Canada, 2004. "Outstanding Student Paper Award".
  • Tech report version: Decentralized Detection and Classification using Kernel Methods. X. Nguyen, M. J. Wainwright and M. I. Jordan. Technical Report 658, Department of Statistics, University of California, Berkeley, April 2004. [ pdf ].

Combinatorial Search, Planning and Constraint Satisfaction

• Planning Graph as the Basis for deriving Heuristics for Plan Synthesis by State Space and CSP Search. X. Nguyen, S. Kambhampati & R. Sanchez-Nigenda. Artificial Intelligence Journal, 135(1-2), 73--124, 2002.
  • AltAlt planner [ homepage ].

• Reviving Partial Order Planning. X. Nguyen and S. Kambhampati, In Proceedings of the 17th International Joint Conference on Artificial Intelligence (IJCAI), Seattle, CA, 459--466, 2001.
  • RePOP planner [ homepage ], its precursor [ UCPOP ] and its "successor" [ VHPOP ].

• AltAlt: Combining the advantages of Graphplan and heuristic state search. R. Sanchez-Nigenda, X. Nguyen and S. Kambhampati, Proceedings of the 3rd International Conference on Knowledge-based Systems (KBCS), Bombay, India, 2000. [ pdf ].
  • Shorter version: AltAlt: Combining Graphplan and heuristic state search. Artificial Intelligence Magazine 22(3), 88--90, 2001.

• Extracting Effective and Admissible State Space Heuristics from the Planning Graph. X. Nguyen and S. Kambhampati, In Proceedings of the 17th National Conference on Artificial Intelligence (AAAI), Austin, TX, 798--805, 2000.

Theses

• Learning in decentralized systems: A nonparametric approach. XuanLong Nguyen, PhD Thesis, University of California, Berkeley, 2007. [ pdf ] (203 pages). Advisors: Michael Jordan and Martin Wainwright . "2007 Leon O. Chua Award" from UC Berkeley for doctoral work.
• Heuristic Search Control for Plan Synthesis Algorithms and Dynamic Constraint Satisfaction Problems (90 pages) [ pdf ]. X. Nguyen, Master Thesis, Arizona State University, Aug 2001. Advisor: Subbarao Kambhampati.