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ORCIDXuanLong Nguyen
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- affiliation: University of Michigan, Department of Statistics
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2020 – today
- 2023
[c36]Aritra Guha, Nhat Ho, XuanLong Nguyen:
On Excess Mass Behavior in Gaussian Mixture Models with Orlicz-Wasserstein Distances. ICML 2023: 11847-11870- [c35]Jiacheng Zhu, Jielin Qiu, Aritra Guha, Zhuolin Yang, XuanLong Nguyen, Bo Li, Ding Zhao:
Interpolation for Robust Learning: Data Augmentation on Wasserstein Geodesics. ICML 2023: 43129-43157 - [c34]Sunrit Chakraborty, Aritra Guha, Rayleigh Lei, XuanLong Nguyen:
Scalable nonparametric Bayesian learning for dynamic velocity fields. UAI 2023: 282-292 - [i28]Jiacheng Zhu, Jielin Qiu, Aritra Guha, Zhuolin Yang, XuanLong Nguyen, Bo Li, Ding Zhao
:
Interpolation for Robust Learning: Data Augmentation on Geodesics. CoRR abs/2302.02092 (2023) - 2022
- [c33]Jiacheng Zhu, Gregory Darnell, Agni Kumar, Ding Zhao, Bo Li, XuanLong Nguyen, Shirley You Ren:
PhysioMTL: Personalizing Physiological Patterns using Optimal Transport Multi-Task Regression. CHIL 2022: 354-374 - [c32]Dat Do, Nhat Ho, XuanLong Nguyen:
Beyond black box densities: Parameter learning for the deviated components. NeurIPS 2022 - [i27]Dat Do, Nhat Ho, XuanLong Nguyen:
Beyond Black Box Densities: Parameter Learning for the Deviated Components. CoRR abs/2202.02651 (2022) - [i26]Jiacheng Zhu, Gregory Darnell, Agni Kumar, Ding Zhao, Bo Li, XuanLong Nguyen, Shirley You Ren:
PhysioMTL: Personalizing Physiological Patterns using Optimal Transport Multi-Task Regression. CoRR abs/2203.12595 (2022) - 2021
- [j15]Viet Huynh, Nhat Ho, Nhan Dam, XuanLong Nguyen, Mikhail Yurochkin, Hung Bui, Dinh Q. Phung:
On efficient multilevel Clustering via Wasserstein distances. J. Mach. Learn. Res. 22: 145:1-145:43 (2021) - [i25]Jiacheng Zhu, Aritra Guha, Mengdi Xu, Yingchen Ma, Rayleigh Lei, Vincenzo Loffredo, XuanLong Nguyen, Ding Zhao:
Functional Optimal Transport: Mapping Estimation and Domain Adaptation for Functional data. CoRR abs/2102.03895 (2021) - [i24]Sunrit Chakraborty, Aritra Guha, Rayleigh Lei, XuanLong Nguyen:
Scalable nonparametric Bayesian learning for heterogeneous and dynamic velocity fields. CoRR abs/2102.07695 (2021) - 2020
- [j14]Mahmoud Abo Khamis, Hung Q. Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich:
Learning Models over Relational Data Using Sparse Tensors and Functional Dependencies. ACM Trans. Database Syst. 45(2): 7:1-7:66 (2020) - [j13]Mahmoud Abo Khamis, Ryan R. Curtin, Benjamin Moseley, Hung Q. Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich:
Functional Aggregate Queries with Additive Inequalities. ACM Trans. Database Syst. 45(4): 17:1-17:41 (2020) - [c31]Ryan R. Curtin, Benjamin Moseley, Hung Q. Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich:
Rk-means: Fast Clustering for Relational Data. AISTATS 2020: 2742-2752 - [i23]Aritra Guha, Rayleigh Lei, Jiacheng Zhu, XuanLong Nguyen, Ding Zhao:
Robust Unsupervised Learning of Temporal Dynamic Interactions. CoRR abs/2006.10241 (2020)
2010 – 2019
- 2019
- [j12]Nhat Ho, XuanLong Nguyen:
Singularity Structures and Impacts on Parameter Estimation in Finite Mixtures of Distributions. SIAM J. Math. Data Sci. 1(4): 730-758 (2019) - [c30]Mikhail Yurochkin, Aritra Guha, Yuekai Sun, XuanLong Nguyen:
Dirichlet Simplex Nest and Geometric Inference. ICML 2019: 7262-7271 - [c29]Mikhail Yurochkin, Zhiwei Fan, Aritra Guha, Paraschos Koutris, XuanLong Nguyen:
Scalable inference of topic evolution via models for latent geometric structures. NeurIPS 2019: 5949-5959 - [c28]Mahmoud Abo Khamis, Ryan R. Curtin, Benjamin Moseley, Hung Q. Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich:
On Functional Aggregate Queries with Additive Inequalities. PODS 2019: 414-431 - [c27]Maximilian Schleich, Dan Olteanu, Mahmoud Abo Khamis, Hung Q. Ngo, XuanLong Nguyen:
A Layered Aggregate Engine for Analytics Workloads. SIGMOD Conference 2019: 1642-1659 - [c26]Maximilian Schleich, Dan Olteanu, Mahmoud Abo Khamis, Hung Q. Ngo, XuanLong Nguyen:
Learning Models over Relational Data: A Brief Tutorial. SUM 2019: 423-432 - [i22]Mikhail Yurochkin, Aritra Guha, Yuekai Sun, XuanLong Nguyen:
Dirichlet Simplex Nest and Geometric Inference. CoRR abs/1905.11009 (2019) - [i21]Maximilian Schleich, Dan Olteanu, Mahmoud Abo Khamis, Hung Q. Ngo, XuanLong Nguyen:
A Layered Aggregate Engine for Analytics Workloads. CoRR abs/1906.08687 (2019) - [i20]Viet Huynh, Nhat Ho, Nhan Dam, XuanLong Nguyen, Mikhail Yurochkin, Hung Bui, Dinh Q. Phung:
On Efficient Multilevel Clustering via Wasserstein Distances. CoRR abs/1909.08787 (2019) - [i19]Ryan R. Curtin, Benjamin Moseley, Hung Q. Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich:
Rk-means: Fast Clustering for Relational Data. CoRR abs/1910.04939 (2019) - [i18]Maximilian Schleich, Dan Olteanu, Mahmoud Abo Khamis, Hung Q. Ngo, XuanLong Nguyen:
Learning Models over Relational Data: A Brief Tutorial. CoRR abs/1911.06577 (2019) - 2018
- [c25]Mahmoud Abo Khamis, Hung Q. Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich:
In-Database Learning with Sparse Tensors. PODS 2018: 325-340 - [c24]Mahmoud Abo Khamis, Hung Q. Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich:
AC/DC: In-Database Learning Thunderstruck. DEEM@SIGMOD 2018: 8:1-8:10 - [i17]Mahmoud Abo Khamis, Hung Q. Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich:
AC/DC: In-Database Learning Thunderstruck. CoRR abs/1803.07480 (2018) - [i16]Mikhail Yurochkin, Zhiwei Fan, Aritra Guha, Paraschos Koutris, XuanLong Nguyen:
Streaming dynamic and distributed inference of latent geometric structures. CoRR abs/1809.08738 (2018) - [i15]Mahmoud Abo Khamis, Ryan R. Curtin, Benjamin Moseley, Hung Q. Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich:
On Functional Aggregate Queries with Additive Inequalities. CoRR abs/1812.09526 (2018) - 2017
- [c23]Hung Q. Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich:
In-Database Factorized Learning. AMW 2017 - [c22]Nhat Ho, XuanLong Nguyen, Mikhail Yurochkin, Hung Hai Bui, Viet Huynh, Dinh Q. Phung:
Multilevel Clustering via Wasserstein Means. ICML 2017: 1501-1509 - [c21]Mikhail Yurochkin, XuanLong Nguyen, Nikolaos Vasiloglou:
Multi-way Interacting Regression via Factorization Machines. NIPS 2017: 2598-2606 - [c20]Mikhail Yurochkin, Aritra Guha, XuanLong Nguyen:
Conic Scan-and-Cover algorithms for nonparametric topic modeling. NIPS 2017: 3878-3887 - [i14]Mahmoud Abo Khamis, Hung Q. Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich:
In-Database Learning with Sparse Tensors. CoRR abs/1703.04780 (2017) - 2016
- [j11]Vijay Manikandan Janakiraman, XuanLong Nguyen, Dennis Assanis:
An ELM based predictive control method for HCCI engines. Eng. Appl. Artif. Intell. 48: 106-118 (2016) - [j10]Vijay Manikandan Janakiraman, XuanLong Nguyen, Dennis Assanis:
Stochastic gradient based extreme learning machines for stable online learning of advanced combustion engines. Neurocomputing 177: 304-316 (2016) - [j9]Hossein Keshavarz, Clayton Scott, XuanLong Nguyen:
On the consistency of inversion-free parameter estimation for Gaussian random fields. J. Multivar. Anal. 150: 245-266 (2016) - [c19]Mikhail Yurochkin, XuanLong Nguyen:
Geometric Dirichlet Means Algorithm for topic inference. NIPS 2016: 2505-2513 - [c18]Viet Huynh, Dinh Q. Phung, Svetha Venkatesh, XuanLong Nguyen, Matthew D. Hoffman, Hung Hai Bui:
Scalable Nonparametric Bayesian Multilevel Clustering. UAI 2016 - [i13]Hossein Keshavarz, Clayton Scott, XuanLong Nguyen:
On the consistency of inversion-free parameter estimation for Gaussian random fields. CoRR abs/1601.03822 (2016) - 2015
- [j8]Vijay Manikandan Janakiraman, XuanLong Nguyen, Jeff Sterniak, Dennis Assanis:
Identification of the Dynamic Operating Envelope of HCCI Engines Using Class Imbalance Learning. IEEE Trans. Neural Networks Learn. Syst. 26(1): 98-112 (2015) - [c17]Viet Huynh, Dinh Q. Phung, XuanLong Nguyen, Svetha Venkatesh, Hung Hai Bui:
Learning Conditional Latent Structures from Multiple Data Sources. PAKDD (1) 2015: 343-354 - [i12]Vijay Manikandan Janakiraman, XuanLong Nguyen, Dennis Assanis:
Nonlinear Model Predictive Control of A Gasoline HCCI Engine Using Extreme Learning Machines. CoRR abs/1501.03969 (2015) - [i11]Vijay Manikandan Janakiraman, XuanLong Nguyen, Dennis Assanis:
Stochastic Gradient Based Extreme Learning Machines For Online Learning of Advanced Combustion Engines. CoRR abs/1501.03975 (2015) - [i10]Hossein Keshavarz, Clayton Scott, XuanLong Nguyen:
Optimal change point detection in Gaussian processes. CoRR abs/1506.01338 (2015) - 2014
- [c16]Jian Tang, Zhaoshi Meng, XuanLong Nguyen, Qiaozhu Mei, Ming Zhang:
Understanding the Limiting Factors of Topic Modeling via Posterior Contraction Analysis. ICML 2014: 190-198 - [c15]Tien-Vu Nguyen, Dinh Quoc Phung, XuanLong Nguyen, Svetha Venkatesh, Hung Bui:
Bayesian Nonparametric Multilevel Clustering with Group-Level Contexts. ICML 2014: 288-296 - [i9]Vu Nguyen, Dinh Q. Phung, XuanLong Nguyen, Svetha Venkatesh, Hung Hai Bui:
Bayesian Nonparametric Multilevel Clustering with Group-Level Contexts. CoRR abs/1401.1974 (2014) - 2013
- [j7]Vijay Manikandan Janakiraman, XuanLong Nguyen, Dennis Assanis:
Nonlinear identification of a gasoline HCCI engine using neural networks coupled with principal component analysis. Appl. Soft Comput. 13(5): 2375-2389 (2013) - [j6]Arash A. Amini, XuanLong Nguyen:
Sequential Detection of Multiple Change Points in Networks: A Graphical Model Approach. IEEE Trans. Inf. Theory 59(9): 5824-5841 (2013) - [c14]Arash A. Amini, XuanLong Nguyen:
Bayesian inference as iterated random functions with applications to sequential inference in graphical models. NIPS 2013: 2922-2930 - [i8]XuanLong Nguyen:
Borrowing strength in hierarchical Bayes: convergence of the Dirichlet base measure. CoRR abs/1301.0802 (2013) - [i7]Vijay Manikandan Janakiraman, XuanLong Nguyen, Jeff Sterniak, Dennis Assanis:
Modeling The Stable Operating Envelope For Partially Stable Combustion Engines Using Class Imbalance Learning. CoRR abs/1306.5702 (2013) - 2012
- [c13]XuanLong Nguyen, Arash A. Amini, Ram Rajagopal:
Message-passing sequential detection of multiple change points in networks. ISIT 2012: 2007-2011 - [i6]XuanLong Nguyen:
Posterior contraction of the population polytope in finite admixture models. CoRR abs/1206.0068 (2012) - 2010
- [j5]XuanLong Nguyen, Martin J. Wainwright, Michael I. Jordan:
Estimating Divergence Functionals and the Likelihood Ratio by Convex Risk Minimization. IEEE Trans. Inf. Theory 56(11): 5847-5861 (2010) - [i5]XuanLong Nguyen:
Inference of global clusters from locally distributed data. CoRR abs/1001.0597 (2010) - [i4]Ram Rajagopal, XuanLong Nguyen, Sinem Coleri Ergen, Pravin Varaiya:
Simultaneous Sequential Detection of Multiple Interacting Faults. CoRR abs/1012.1258 (2010)
2000 – 2009
- 2008
- [j4]XuanLong Nguyen, Martin J. Wainwright, Michael I. Jordan:
On Optimal Quantization Rules for Some Problems in Sequential Decentralized Detection. IEEE Trans. Inf. Theory 54(7): 3285-3295 (2008) - [c12]Ram Rajagopal, XuanLong Nguyen, Sinem Coleri Ergen, Pravin Varaiya:
Distributed Online Simultaneous Fault Detection for Multiple Sensors. IPSN 2008: 133-144 - [c11]XuanLong Nguyen, Ling Huang, Anthony D. Joseph:
Support Vector Machines, Data Reduction, and Approximate Kernel Matrices. ECML/PKDD (2) 2008: 137-153 - [i3]XuanLong Nguyen, Martin J. Wainwright, Michael I. Jordan:
Estimating divergence functionals and the likelihood ratio by convex risk minimization. CoRR abs/0809.0853 (2008) - 2007
- [c10]Ling Huang, XuanLong Nguyen, Minos N. Garofalakis, Joseph M. Hellerstein, Michael I. Jordan, Anthony D. Joseph, Nina Taft:
Communication-Efficient Online Detection of Network-Wide Anomalies. INFOCOM 2007: 134-142 - [c9]XuanLong Nguyen, Martin J. Wainwright, Michael I. Jordan:
Nonparametric estimation of the likelihood ratio and divergence functionals. ISIT 2007: 2016-2020 - [c8]XuanLong Nguyen, Martin J. Wainwright, Michael I. Jordan:
Estimating divergence functionals and the likelihood ratio by penalized convex risk minimization. NIPS 2007: 1089-1096 - 2006
- [c7]XuanLong Nguyen, Martin J. Wainwright, Michael I. Jordan:
On optimal quantization rules for sequential decision problems. ISIT 2006: 2652-2656 - [c6]Ling Huang, XuanLong Nguyen, Minos N. Garofalakis, Michael I. Jordan, Anthony D. Joseph, Nina Taft:
In-Network PCA and Anomaly Detection. NIPS 2006: 617-624 - [i2]XuanLong Nguyen, Martin J. Wainwright, Michael I. Jordan:
On optimal quantization rules for some sequential decision problems. CoRR abs/math/0608556 (2006) - 2005
- [j3]XuanLong Nguyen, Michael I. Jordan, Bruno Sinopoli:
A kernel-based learning approach to ad hoc sensor network localization. ACM Trans. Sens. Networks 1(1): 134-152 (2005) - [j2]XuanLong Nguyen, Martin J. Wainwright, Michael I. Jordan:
Nonparametric decentralized detection using kernel methods. IEEE Trans. Signal Process. 53(11): 4053-4066 (2005) - [c5]XuanLong Nguyen, Martin J. Wainwright, Michael I. Jordan:
Divergences, surrogate loss functions and experimental design. NIPS 2005: 1011-1018 - [i1]XuanLong Nguyen, Martin J. Wainwright, Michael I. Jordan:
On divergences, surrogate loss functions, and decentralized detection. CoRR abs/math/0510521 (2005) - 2004
- [c4]XuanLong Nguyen, Martin J. Wainwright, Michael I. Jordan:
Decentralized detection and classification using kernel methods. ICML 2004 - 2003
- [c3]XuanLong Nguyen, Michael I. Jordan:
On the Concentration of Expectation and Approximate Inference in Layered Networks. NIPS 2003: 393-400 - 2002
- [j1]XuanLong Nguyen, Subbarao Kambhampati, Romeo Sanchez Nigenda:
Planning graph as the basis for deriving heuristics for plan synthesis by state space and CSP search. Artif. Intell. 135(1-2): 73-123 (2002) - 2001
- [c2]XuanLong Nguyen, Subbarao Kambhampati:
Reviving Partial Order Planning. IJCAI 2001: 459-466 - 2000
- [c1]XuanLong Nguyen, Subbarao Kambhampati:
Extracting Effective and Admissible State Space Heuristics from the Planning Graph. AAAI/IAAI 2000: 798-805
Coauthor Index
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