X. Nguyen

发表

Nonparametric estimation of the likelihood ratio and divergence functionals

Martin J. Wainwright, Michael I. Jordan, XuanLong Nguyen, 2007, 2007 IEEE International Symposium on Information Theory.

ON surrogate loss functions and f-divergences

Martin J. Wainwright, Michael I. Jordan, XuanLong Nguyen, 2005, math/0510521.

Nonparametric decentralized detection using kernel methods

Michael I. Jordan, M. Wainwright, X. Nguyen, 2005, IEEE Transactions on Signal Processing.

A kernel-based learning approach to ad hoc sensor network localization

Bruno Sinopoli, Michael I. Jordan, XuanLong Nguyen, 2005, TOSN.

On posterior contraction of parameters and interpretability in Bayesian mixture modeling

Nhat Ho, X. Nguyen, Aritra Guha, 2019, Bernoulli.

On divergences, surrogate loss functions, and decentralized detection pdf

Martin J. Wainwright, Michael I. Jordan, XuanLong Nguyen, 2005, ArXiv.

On distance measures, surrogate loss functions, and distributed detection

Michael I. Jordan, M. Wainwright, X. Nguyen, 2005 .

Identifiability and optimal rates of convergence for parameters of multiple types in finite mixtures

Nhat Ho, X. Nguyen, 2015, 1501.02497.

Multilevel Clustering via Wasserstein Means

Dinh Q. Phung, Nhat Ho, Hung Hai Bui, 2017, ICML.

Estimating Divergence Functionals and the Likelihood Ratio by Convex Risk Minimization

Martin J. Wainwright, Michael I. Jordan, XuanLong Nguyen, 2008, IEEE Transactions on Information Theory.

Convergence rates of parameter estimation for some weakly identifiable finite mixtures

Nhat Ho, X. Nguyen, 2016 .

On strong identifiability and convergence rates of parameter estimation in finite mixtures

Nhat Ho, X. Nguyen, 2016 .

On Optimal Quantization Rules for Some Problems in Sequential Decentralized Detection

Martin J. Wainwright, Michael I. Jordan, XuanLong Nguyen, 2006, IEEE Transactions on Information Theory.

Estimating divergence functionals and the likelihood ratio by penalized convex risk minimization

Martin J. Wainwright, Michael I. Jordan, XuanLong Nguyen, 2007, NIPS.

In-Network PCA and Anomaly Detection

Ling Huang, Michael I. Jordan, Minos N. Garofalakis, 2006, NIPS.

Posterior contraction of the population polytope in finite admixture models pdf

XuanLong Nguyen, X. Nguyen, 2012, ArXiv.

Scalable Nonparametric Bayesian Multilevel Clustering

Svetha Venkatesh, Dinh Q. Phung, Matthew D. Hoffman, 2016, UAI.

Conditionally Dependent Dirichlet Processes for Modelling Naturally Correlated Data Sources

Dinh Q. Phung, X. Nguyen, S. Venkatesh, 2013 .

On Functional Aggregate Queries with Additive Inequalities

Benjamin Moseley, Hung Q. Ngo, Dan Olteanu, 2018, PODS.

The Dirichlet labeling process for functional data analysis

A. Gelfand, X. Nguyen, 2008 .

Simultaneous Sequential Detection of Multiple Interacting Faults pdf

Pravin Varaiya, Ram Rajagopal, Sinem Coleri Ergen, 2010, ArXiv.

An ELM based predictive control method for HCCI engines

XuanLong Nguyen, Vijay Manikandan Janakiraman, Dennis Assanis, 2016, Eng. Appl. Artif. Intell..

A System Identification Framework for Modeling Complex Combustion Dynamics Using Support Vector Machines

XuanLong Nguyen, Jeff Sterniak, Dennis N. Assanis, 2014, ICINCO 2014.

In-Database Learning with Sparse Tensors

Dan Olteanu, XuanLong Nguyen, Mahmoud Abo Khamis, 2017, PODS.

Convergence of latent mixing measures in finite and infinite mixture models

X. Nguyen, 2011, 1109.3250.

Robust estimation of mixing measures in finite mixture models

Y. Ritov, Nhat Ho, X. Nguyen, 2017, Bernoulli.

Bayesian Analysis of RNA-Seq Data Using a Family of Negative Binomial Models.

X. Nguyen, Weisheng Wu, Hui Jiang, 2017, Bayesian analysis.

Rk-means: Fast Clustering for Relational Data: Supplementary Material

Ryan R. Curtin, X. Nguyen, Benjamin Moseley, 2020 .

Lectures on Bayesian nonparametrics: modeling, algorithms and some theory

X. Nguyen, 2015 .

Local inversion-free estimation of spatial Gaussian processes

X. Nguyen, C. Scott, Hossein Keshavarz, 2018, Electronic Journal of Statistics.

RATES OF PARAMETER ESTIMATION 39

X. Nguyen, 2016 .

On strong identifiability and optimal rates of parameter estimation in finite mixtures

Nhat Ho, X. Nguyen, 2015 .

OPTIMAL RATES OF PARAMETER ESTIMATION FOR SOME WEAKLY IDENTIFIABLE FINITE MIXTURES BY NHAT HO

X. Nguyen, 2015 .

Supplementary Material for Bayesian Nonparametric Multilevel Clustering with Contexts

Dinh Q. Phung, X. Nguyen, S. Venkatesh, 2014 .

Supplementary material for “Scalable Nonparametric Bayesian Multilevel Clustering”

Dinh Q. Phung, X. Nguyen, S. Venkatesh, 2016 .

On strong identiﬁability and convergence rates of parameter estimation in ﬁnite mixtures

Nhat Ho, X. Nguyen, 2016 .

Borrowing strengh in hierarchical Bayes: Posterior concentration of the Dirichlet base measure

X. Nguyen, 2016 .

On the consistency of inversion-free parameter estimation for Gaussian random ﬁelds (cid:73)

X. Nguyen, C. Scott, Hossein Keshavarz, 2016 .

Supplementary material for Dirichlet Simplex Nest and Geometric Inference

X. Nguyen, Aritra Guha, Yuekai Sun, 2019 .

Modeling Random Directions in 2D Simplex Data

X. Nguyen, Rayleigh Lei, 2021, 2103.12214.

Beyond Black Box Densities: Parameter Learning for the Deviated Components

Nhat Ho, X. Nguyen, Dat Do, 2022, NeurIPS.

Strong identifiability and parameter learning in regression with heterogeneous response

X. Nguyen, L. Do, Dat Do, 2022, 2212.04091.

Nonlinear identification of a gasoline HCCI engine using neural networks coupled with principal component analysis

XuanLong Nguyen, Vijay Manikandan Janakiraman, Dennis Assanis, 2013, Appl. Soft Comput..

Geometric Dirichlet Means Algorithm for topic inference

XuanLong Nguyen, Mikhail Yurochkin, X. Nguyen, 2016, NIPS.

Singularity Structures and Impacts on Parameter Estimation in Finite Mixtures of Distributions

Nhat Ho, XuanLong Nguyen, Nhat Ho, 2016, SIAM J. Math. Data Sci..

Wasserstein distances for discrete measures and convergence in nonparametric mixture models 1

X. Nguyen, 2011 .

Multi-way Interacting Regression via Factorization Machines

XuanLong Nguyen, Mikhail Yurochkin, Nikolaos Vasiloglou, 2017, NIPS.

Convergence of de Finetti’s mixing measure in latent structure models for observed exchangeable sequences

X. Nguyen, Yun Wei, 2020, The Annals of Statistics.

Graphically dependent and spatially varying Dirichlet process mixtures

XuanLong Nguyen, X. Nguyen, 2010 .

Inference of global clusters from locally distributed data pdf

XuanLong Nguyen, X. Nguyen, 2010, ArXiv.

Understanding the Limiting Factors of Topic Modeling via Posterior Contraction Analysis

Qiaozhu Mei, Ming Zhang, XuanLong Nguyen, 2014, ICML.

Scalable nonparametric Bayesian learning for heterogeneous and dynamic velocity fields pdf

XuanLong Nguyen, Aritra Guha, Rayleigh Lei, 2021, ArXiv.

Robust Unsupervised Learning of Temporal Dynamic Interactions pdf

Ding Zhao, Aritra Guha, Jiacheng Zhu, 2020, ArXiv.

Learning Models over Relational Data Using Sparse Tensors and Functional Dependencies

Mahmoud Abo Khamis, X. Nguyen, H. Ngo, 2017, ACM Trans. Database Syst..

Identification of the Dynamic Operating Envelope of HCCI Engines Using Class Imbalance Learning

XuanLong Nguyen, Jeff Sterniak, Vijay Manikandan Janakiraman, 2015, IEEE Transactions on Neural Networks and Learning Systems.

Distributed PCA and Network Anomaly Detection

Ling Huang, Michael I. Jordan, Anthony D. Joseph, 2006 .

Convergence of latent mixing measures in nonparametric and mixture models

X. Nguyen, 2011 .

Minimum $\Phi$-distance estimators for finite mixing measures

X. Nguyen, Sayan Mukherjee, Yun-Chun Wei, 2023, 2304.10052.

The Dirichlet labeling process for clustering functional data

Alan E. Gelfand, XuanLong Nguyen, A. Gelfand, 2011 .

Interpolation for Robust Learning: Data Augmentation on Geodesics

X. Nguyen, Aritra Guha, Bo Li, 2023, ArXiv.

Stochastic gradient based extreme learning machines for stable online learning of advanced combustion engines

XuanLong Nguyen, Vijay Manikandan Janakiraman, Dennis Assanis, 2016, Neurocomputing.

Stochastic Gradient Based Extreme Learning Machines For Online Learning of Advanced Combustion Engines pdf

XuanLong Nguyen, Vijay Manikandan Janakiraman, Dennis Assanis, 2015, ArXiv.

Nonlinear Model Predictive Control of A Gasoline HCCI Engine Using Extreme Learning Machines pdf

XuanLong Nguyen, Vijay Manikandan Janakiraman, Dennis Assanis, 2015, ArXiv.

Modeling The Stable Operating Envelope For Partially Stable Combustion Engines Using Class Imbalance Learning pdf

XuanLong Nguyen, Jeff Sterniak, Vijay Manikandan Janakiraman, 2013, ArXiv.

Hedging of Contingent Claims in Incomplete Markets

X. Nguyen, 2002 .

A Layered Aggregate Engine for Analytics Workloads

Dan Olteanu, XuanLong Nguyen, Mahmoud Abo Khamis, 2019, SIGMOD Conference.

On optimal quantization rules for sequential decision problems

Martin J. Wainwright, Michael I. Jordan, XuanLong Nguyen, 2006, 2006 IEEE International Symposium on Information Theory.

Learning in decentralized systems: a nonparametric approach

Michael I. Jordan, XuanLong Nguyen, X. Nguyen, 2007 .

Functional optimal transport: map estimation and domain adaptation for functional data

X. Nguyen, Aritra Guha, Ding Zhao, 2021, 2102.03895.

On the consistency of inversion-free parameter estimation for Gaussian random fields

XuanLong Nguyen, Clayton Scott, Hossein Keshavarz, 2016, J. Multivar. Anal..

Communication-Efficient Online Detection of Network-Wide Anomalies

Ling Huang, Michael I. Jordan, Joseph M. Hellerstein, 2007, IEEE INFOCOM 2007 - 26th IEEE International Conference on Computer Communications.

On Efficient Multilevel Clustering via Wasserstein Distances

Dinh Q. Phung, Nhat Ho, X. Nguyen, 2019, J. Mach. Learn. Res..

Optimal change point detection in Gaussian processes pdf

XuanLong Nguyen, Clayton Scott, Hossein Keshavarz, 2015, ArXiv.

In-Database Learning with Sparse Tensors

Hung Q. Ngo, Dan Olteanu, XuanLong Nguyen, 2017, PODS.

Functional Aggregate Queries with Additive Inequalities

Benjamin Moseley, Dan Olteanu, Ryan R. Curtin, 2018, ACM Trans. Database Syst..

Scalable inference of topic evolution via models for latent geometric structures

Paraschos Koutris, XuanLong Nguyen, Mikhail Yurochkin, 2018, NeurIPS.

Streaming dynamic and distributed inference of latent geometric structures pdf

Paraschos Koutris, XuanLong Nguyen, Mikhail Yurochkin, 2018, ArXiv.

Rk-means: Fast Clustering for Relational Data

Hung Q. Ngo, Dan Olteanu, Ryan R. Curtin, 2019, AISTATS.

AC/DC: In-Database Learning Thunderstruck

Mahmoud Abo Khamis, X. Nguyen, H. Ngo, 2018, DEEM@SIGMOD.

Interpolation for Robust Learning: Data Augmentation on Wasserstein Geodesics

X. Nguyen, Aritra Guha, Bo Li, 2023, ICML.

PhysioMTL: Personalizing Physiological Patterns using Optimal Transport Multi-Task Regression

X. Nguyen, Bo Li, Ding Zhao, 2022, CHIL.

Functional optimal transport: map estimation and domain adaptation for functional data

X. Nguyen, Aritra Guha, Ding Zhao, 2021, 2102.03895.

Interpolation for Robust Learning: Data Augmentation on Geodesics

X. Nguyen, Aritra Guha, Bo Li, 2023, ArXiv.

Bayesian inference as iterated random functions with applications to sequential inference in graphical models

XuanLong Nguyen, Arash A. Amini, X. Nguyen, 2013, NIPS.

Sequential Detection of Multiple Change Points in Networks: A Graphical Model Approach

XuanLong Nguyen, Arash A. Amini, X. Nguyen, 2012, IEEE Transactions on Information Theory.

Message-passing sequential detection of multiple change points in networks

Ram Rajagopal, XuanLong Nguyen, Arash A. Amini, 2012, 2012 IEEE International Symposium on Information Theory Proceedings.

Bayesian Nonparametric Multilevel Clustering with Group-Level Contexts pdf

Dinh Q. Phung, Hung Hai Bui, Svetha Venkatesh, 2014, ICML.

Decentralized detection and classification using kernel methods

Martin J. Wainwright, Michael I. Jordan, XuanLong Nguyen, 2004, ICML.

Dirichlet Simplex Nest and Geometric Inference

XuanLong Nguyen, Yuekai Sun, Mikhail Yurochkin, 2019, ICML.

Anomaly Detection in Distributed Dataflow Systems

X. Nguyen, Xuan Truong NGUYEN, 2016 .

Bayesian Analysis of RNA-Seq Data Using a Family of Negative Binomial Models.

X. Nguyen, Weisheng Wu, Hui Jiang, 2017, Bayesian analysis.