XuanLong Nguyen

Publication Activity (10 Years)

Years Active: 2000-2023
Publications (10 Years): 42

Top Topics

Extreme Learning Machine

Nonparametric Bayesian

Relational Data

Top Venues

Publications

Jiacheng Zhu, Jielin Qiu, Aritra Guha, Zhuolin Yang, XuanLong Nguyen, Bo Li, Ding Zhao
Interpolation for Robust Learning: Data Augmentation on Geodesics. CoRR (2023)
Sunrit Chakraborty, Aritra Guha, Rayleigh Lei, XuanLong Nguyen
Scalable nonparametric Bayesian learning for dynamic velocity fields. UAI (2023)
Aritra Guha, Nhat Ho, XuanLong Nguyen
On Excess Mass Behavior in Gaussian Mixture Models with Orlicz-Wasserstein Distances. ICML (2023)
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)
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 (2022)
Dat Do, Nhat Ho, XuanLong Nguyen
Beyond Black Box Densities: Parameter Learning for the Deviated Components. CoRR (2022)
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)
Dat Do, Nhat Ho, XuanLong Nguyen
Beyond black box densities: Parameter learning for the deviated components. NeurIPS (2022)
Sunrit Chakraborty, Aritra Guha, Rayleigh Lei, XuanLong Nguyen
Scalable nonparametric Bayesian learning for heterogeneous and dynamic velocity fields. CoRR (2021)
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 (2021)
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 (2021)
Ryan R. Curtin, Benjamin Moseley, Hung Q. Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich
Rk-means: Fast Clustering for Relational Data. AISTATS (2020)
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) (2020)
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) (2020)
Aritra Guha, Rayleigh Lei, Jiacheng Zhu, XuanLong Nguyen, Ding Zhao
Robust Unsupervised Learning of Temporal Dynamic Interactions. CoRR (2020)
Mikhail Yurochkin, Aritra Guha, Yuekai Sun, XuanLong Nguyen
Dirichlet Simplex Nest and Geometric Inference. ICML (2019)
Maximilian Schleich, Dan Olteanu, Mahmoud Abo Khamis, Hung Q. Ngo, XuanLong Nguyen
Learning Models over Relational Data: A Brief Tutorial. CoRR (2019)
Ryan R. Curtin, Benjamin Moseley, Hung Q. Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich
Rk-means: Fast Clustering for Relational Data. CoRR (2019)
Mikhail Yurochkin, Aritra Guha, Yuekai Sun, XuanLong Nguyen
Dirichlet Simplex Nest and Geometric Inference. CoRR (2019)
Nhat Ho, XuanLong Nguyen
Singularity Structures and Impacts on Parameter Estimation in Finite Mixtures of Distributions. SIAM J. Math. Data Sci. 1 (4) (2019)
Viet Huynh, Nhat Ho, Nhan Dam, XuanLong Nguyen, Mikhail Yurochkin, Hung Bui, Dinh Q. Phung
On Efficient Multilevel Clustering via Wasserstein Distances. CoRR (2019)
Maximilian Schleich, Dan Olteanu, Mahmoud Abo Khamis, Hung Q. Ngo, XuanLong Nguyen
A Layered Aggregate Engine for Analytics Workloads. SIGMOD Conference (2019)
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)
Maximilian Schleich, Dan Olteanu, Mahmoud Abo Khamis, Hung Q. Ngo, XuanLong Nguyen
Learning Models over Relational Data: A Brief Tutorial. SUM (2019)
Mikhail Yurochkin, Zhiwei Fan, Aritra Guha, Paraschos Koutris, XuanLong Nguyen
Scalable inference of topic evolution via models for latent geometric structures. NeurIPS (2019)
Maximilian Schleich, Dan Olteanu, Mahmoud Abo Khamis, Hung Q. Ngo, XuanLong Nguyen
A Layered Aggregate Engine for Analytics Workloads. CoRR (2019)
Mahmoud Abo Khamis, Hung Q. Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich
AC/DC: In-Database Learning Thunderstruck. DEEM@SIGMOD (2018)
Mahmoud Abo Khamis, Hung Q. Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich
AC/DC: In-Database Learning Thunderstruck. CoRR (2018)
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 (2018)
Mahmoud Abo Khamis, Hung Q. Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich
In-Database Learning with Sparse Tensors. PODS (2018)
Mikhail Yurochkin, Zhiwei Fan, Aritra Guha, Paraschos Koutris, XuanLong Nguyen
Streaming dynamic and distributed inference of latent geometric structures. CoRR (2018)
Hung Q. Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich
In-Database Factorized Learning. AMW (2017)
Nhat Ho, XuanLong Nguyen, Mikhail Yurochkin, Hung Hai Bui, Viet Huynh, Dinh Q. Phung
Multilevel Clustering via Wasserstein Means. ICML (2017)
Mahmoud Abo Khamis, Hung Q. Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich
In-Database Learning with Sparse Tensors. CoRR (2017)
Mikhail Yurochkin, XuanLong Nguyen, Nikolaos Vasiloglou
Multi-way Interacting Regression via Factorization Machines. NIPS (2017)
Mikhail Yurochkin, Aritra Guha, XuanLong Nguyen
Conic Scan-and-Cover algorithms for nonparametric topic modeling. NIPS (2017)
Hossein Keshavarz, Clayton Scott, XuanLong Nguyen
On the consistency of inversion-free parameter estimation for Gaussian random fields. J. Multivar. Anal. 150 (2016)
Vijay Manikandan Janakiraman, XuanLong Nguyen, Dennis Assanis
An ELM based predictive control method for HCCI engines. Eng. Appl. Artif. Intell. 48 (2016)
Viet Huynh, Dinh Q. Phung, Svetha Venkatesh, XuanLong Nguyen, Matthew D. Hoffman, Hung Hai Bui
Scalable Nonparametric Bayesian Multilevel Clustering. UAI (2016)
Mikhail Yurochkin, XuanLong Nguyen
Geometric Dirichlet Means Algorithm for topic inference. NIPS (2016)
Hossein Keshavarz, Clayton Scott, XuanLong Nguyen
On the consistency of inversion-free parameter estimation for Gaussian random fields. CoRR (2016)
Vijay Manikandan Janakiraman, XuanLong Nguyen, Dennis Assanis
Stochastic gradient based extreme learning machines for stable online learning of advanced combustion engines. Neurocomputing 177 (2016)
Vijay Manikandan Janakiraman, XuanLong Nguyen, Dennis Assanis
Stochastic Gradient Based Extreme Learning Machines For Online Learning of Advanced Combustion Engines. CoRR (2015)
Vijay Manikandan Janakiraman, XuanLong Nguyen, Dennis Assanis
Nonlinear Model Predictive Control of A Gasoline HCCI Engine Using Extreme Learning Machines. CoRR (2015)
Hossein Keshavarz, Clayton Scott, XuanLong Nguyen
Optimal change point detection in Gaussian processes. CoRR (2015)
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) (2015)
Viet Huynh, Dinh Q. Phung, XuanLong Nguyen, Svetha Venkatesh, Hung Hai Bui
Learning Conditional Latent Structures from Multiple Data Sources. PAKDD (1) (2015)
Jian Tang, Zhaoshi Meng, XuanLong Nguyen, Qiaozhu Mei, Ming Zhang
Understanding the Limiting Factors of Topic Modeling via Posterior Contraction Analysis. ICML (2014)
Tien-Vu Nguyen, Dinh Quoc Phung, XuanLong Nguyen, Svetha Venkatesh, Hung Hai Bui
Bayesian Nonparametric Multilevel Clustering with Group-Level Contexts. ICML (2014)
Vu Nguyen, Dinh Q. Phung, XuanLong Nguyen, Svetha Venkatesh, Hung Hai Bui
Bayesian Nonparametric Multilevel Clustering with Group-Level Contexts. CoRR (2014)
Arash A. Amini, XuanLong Nguyen
Sequential Detection of Multiple Change Points in Networks: A Graphical Model Approach. IEEE Trans. Inf. Theory 59 (9) (2013)
Vijay Manikandan Janakiraman, XuanLong Nguyen, Jeff Sterniak, Dennis Assanis
Modeling The Stable Operating Envelope For Partially Stable Combustion Engines Using Class Imbalance Learning. CoRR (2013)
Arash A. Amini, XuanLong Nguyen
Bayesian inference as iterated random functions with applications to sequential inference in graphical models. NIPS (2013)
XuanLong Nguyen
Borrowing strength in hierarchical Bayes: convergence of the Dirichlet base measure CoRR (2013)
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) (2013)
XuanLong Nguyen, Arash A. Amini, Ram Rajagopal
Message-passing sequential detection of multiple change points in networks. ISIT (2012)
XuanLong Nguyen
Posterior contraction of the population polytope in finite admixture models CoRR (2012)
XuanLong Nguyen
Inference of global clusters from locally distributed data. CoRR (2010)
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) (2010)
Ram Rajagopal, XuanLong Nguyen, Sinem Coleri Ergen, Pravin Varaiya
Simultaneous Sequential Detection of Multiple Interacting Faults CoRR (2010)
Ram Rajagopal, XuanLong Nguyen, Sinem Coleri Ergen, Pravin Varaiya
Distributed Online Simultaneous Fault Detection for Multiple Sensors. IPSN (2008)
XuanLong Nguyen, Martin J. Wainwright, Michael I. Jordan
Estimating divergence functionals and the likelihood ratio by convex risk minimization CoRR (2008)
XuanLong Nguyen, Ling Huang, Anthony D. Joseph
Support Vector Machines, Data Reduction, and Approximate Kernel Matrices. ECML/PKDD (2) (2008)
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) (2008)
XuanLong Nguyen, Martin J. Wainwright, Michael I. Jordan
Estimating divergence functionals and the likelihood ratio by penalized convex risk minimization. NIPS (2007)
XuanLong Nguyen, Martin J. Wainwright, Michael I. Jordan
Nonparametric estimation of the likelihood ratio and divergence functionals. ISIT (2007)
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)
XuanLong Nguyen, Martin J. Wainwright, Michael I. Jordan
On optimal quantization rules for some sequential decision problems CoRR (2006)
Ling Huang, XuanLong Nguyen, Minos N. Garofalakis, Michael I. Jordan, Anthony D. Joseph, Nina Taft
In-Network PCA and Anomaly Detection. NIPS (2006)
XuanLong Nguyen, Martin J. Wainwright, Michael I. Jordan
On optimal quantization rules for sequential decision problems. ISIT (2006)
XuanLong Nguyen, Martin J. Wainwright, Michael I. Jordan
Divergences, surrogate loss functions and experimental design. NIPS (2005)
XuanLong Nguyen, Michael I. Jordan, Bruno Sinopoli
A kernel-based learning approach to ad hoc sensor network localization. ACM Trans. Sens. Networks 1 (1) (2005)
XuanLong Nguyen, Martin J. Wainwright, Michael I. Jordan
On divergences, surrogate loss functions, and decentralized detection CoRR (2005)
XuanLong Nguyen, Martin J. Wainwright, Michael I. Jordan
Nonparametric decentralized detection using kernel methods. IEEE Trans. Signal Process. 53 (11) (2005)
XuanLong Nguyen, Martin J. Wainwright, Michael I. Jordan
Decentralized detection and classification using kernel methods. ICML (2004)
XuanLong Nguyen, Michael I. Jordan
On the Concentration of Expectation and Approximate Inference in Layered Networks. NIPS (2003)
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) (2002)
XuanLong Nguyen, Subbarao Kambhampati
Reviving Partial Order Planning. IJCAI (2001)
XuanLong Nguyen, Subbarao Kambhampati
Extracting Effective and Admissible State Space Heuristics from the Planning Graph. AAAI/IAAI (2000)