XuanLong Nguyen

81 papers A* 13A 3B 3Journal 44Unranked 18

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	Functional optimal transport: regularized map estimation and domain adaptation for functional data. J. Mach. Learn. Res. Jiacheng Zhu, Aritra Guha, Dat Do, Mengdi Xu, XuanLong Nguyen, Ding Zhao
2023	J	`jnl`	Interpolation for Robust Learning: Data Augmentation on Geodesics. CoRR Jiacheng Zhu, Jielin Qiu, Aritra Guha, Zhuolin Yang, XuanLong Nguyen, Bo Li, Ding Zhao
2023	A*	`conf`	Interpolation for Robust Learning: Data Augmentation on Wasserstein Geodesics. ICML Jiacheng Zhu, Jielin Qiu, Aritra Guha, Zhuolin Yang, XuanLong Nguyen, Bo Li, Ding Zhao
2023	A*	`conf`	On Excess Mass Behavior in Gaussian Mixture Models with Orlicz-Wasserstein Distances. ICML Aritra Guha, Nhat Ho, XuanLong Nguyen
2023	A	`conf`	Scalable nonparametric Bayesian learning for dynamic velocity fields. UAI Sunrit Chakraborty, Aritra Guha, Rayleigh Lei, XuanLong Nguyen
2022	J	`jnl`	Beyond Black Box Densities: Parameter Learning for the Deviated Components. CoRR Dat Do, Nhat Ho, XuanLong Nguyen
2022	A*	`conf`	Beyond black box densities: Parameter learning for the deviated components. NeurIPS Dat Do, Nhat Ho, XuanLong Nguyen
2022	—	`conf`	PhysioMTL: Personalizing Physiological Patterns using Optimal Transport Multi-Task Regression. CHIL Jiacheng Zhu, Gregory Darnell, Agni Kumar, Ding Zhao, Bo Li, XuanLong Nguyen, Shirley You Ren
2022	J	`jnl`	PhysioMTL: Personalizing Physiological Patterns using Optimal Transport Multi-Task Regression. CoRR Jiacheng Zhu, Gregory Darnell, Agni Kumar, Ding Zhao, Bo Li, XuanLong Nguyen, Shirley You Ren
2021	J	`jnl`	Functional Optimal Transport: Mapping Estimation and Domain Adaptation for Functional data. CoRR Jiacheng Zhu, Aritra Guha, Mengdi Xu, Yingchen Ma, Rayleigh Lei, Vincenzo Loffredo, XuanLong Nguyen, Ding Zhao
2021	J	`jnl`	On efficient multilevel Clustering via Wasserstein distances. J. Mach. Learn. Res. Viet Huynh, Nhat Ho, Nhan Dam, XuanLong Nguyen, Mikhail Yurochkin, Hung Bui, Dinh Q. Phung
2021	J	`jnl`	Scalable nonparametric Bayesian learning for heterogeneous and dynamic velocity fields. CoRR Sunrit Chakraborty, Aritra Guha, Rayleigh Lei, XuanLong Nguyen
2020	J	`jnl`	Functional Aggregate Queries with Additive Inequalities. ACM Trans. Database Syst. Mahmoud Abo Khamis, Ryan R. Curtin, Benjamin Moseley, Hung Q. Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich
2020	J	`jnl`	Learning Models over Relational Data Using Sparse Tensors and Functional Dependencies. ACM Trans. Database Syst. Mahmoud Abo Khamis, Hung Q. Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich
2020	A	`conf`	Rk-means: Fast Clustering for Relational Data. AISTATS Ryan R. Curtin, Benjamin Moseley, Hung Q. Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich
2020	J	`jnl`	Robust Unsupervised Learning of Temporal Dynamic Interactions. CoRR Aritra Guha, Rayleigh Lei, Jiacheng Zhu, XuanLong Nguyen, Ding Zhao
2019	—	`conf`	A Layered Aggregate Engine for Analytics Workloads. SIGMOD Conference Maximilian Schleich, Dan Olteanu, Mahmoud Abo Khamis, Hung Q. Ngo, XuanLong Nguyen
2019	J	`jnl`	A Layered Aggregate Engine for Analytics Workloads. CoRR Maximilian Schleich, Dan Olteanu, Mahmoud Abo Khamis, Hung Q. Ngo, XuanLong Nguyen
2019	A*	`conf`	Dirichlet Simplex Nest and Geometric Inference. ICML Mikhail Yurochkin, Aritra Guha, Yuekai Sun, XuanLong Nguyen
2019	J	`jnl`	Dirichlet Simplex Nest and Geometric Inference. CoRR Mikhail Yurochkin, Aritra Guha, Yuekai Sun, XuanLong Nguyen
2019	—	`conf`	Learning Models over Relational Data: A Brief Tutorial. SUM Maximilian Schleich, Dan Olteanu, Mahmoud Abo Khamis, Hung Q. Ngo, XuanLong Nguyen
2019	J	`jnl`	Learning Models over Relational Data: A Brief Tutorial. CoRR Maximilian Schleich, Dan Olteanu, Mahmoud Abo Khamis, Hung Q. Ngo, XuanLong Nguyen
2019	J	`jnl`	On Efficient Multilevel Clustering via Wasserstein Distances. CoRR Viet Huynh, Nhat Ho, Nhan Dam, XuanLong Nguyen, Mikhail Yurochkin, Hung Bui, Dinh Q. Phung
2019	A*	`conf`	On Functional Aggregate Queries with Additive Inequalities. PODS Mahmoud Abo Khamis, Ryan R. Curtin, Benjamin Moseley, Hung Q. Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich
2019	J	`jnl`	Rk-means: Fast Clustering for Relational Data. CoRR Ryan R. Curtin, Benjamin Moseley, Hung Q. Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich
2019	A*	`conf`	Scalable inference of topic evolution via models for latent geometric structures. NeurIPS Mikhail Yurochkin, Zhiwei Fan, Aritra Guha, Paraschos Koutris, XuanLong Nguyen
2019	J	`jnl`	Singularity Structures and Impacts on Parameter Estimation in Finite Mixtures of Distributions. SIAM J. Math. Data Sci. Nhat Ho, XuanLong Nguyen
2018	—	`conf`	AC/DC: In-Database Learning Thunderstruck. DEEM@SIGMOD Mahmoud Abo Khamis, Hung Q. Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich
2018	J	`jnl`	AC/DC: In-Database Learning Thunderstruck. CoRR Mahmoud Abo Khamis, Hung Q. Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich
2018	A*	`conf`	In-Database Learning with Sparse Tensors. PODS Mahmoud Abo Khamis, Hung Q. Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich
2018	J	`jnl`	On Functional Aggregate Queries with Additive Inequalities. CoRR Mahmoud Abo Khamis, Ryan R. Curtin, Benjamin Moseley, Hung Q. Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich
2018	J	`jnl`	Streaming dynamic and distributed inference of latent geometric structures. CoRR Mikhail Yurochkin, Zhiwei Fan, Aritra Guha, Paraschos Koutris, XuanLong Nguyen
2017	—	`conf`	Conic Scan-and-Cover algorithms for nonparametric topic modeling. NIPS Mikhail Yurochkin, Aritra Guha, XuanLong Nguyen
2017	—	`conf`	In-Database Factorized Learning. AMW Hung Q. Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich
2017	J	`jnl`	In-Database Learning with Sparse Tensors. CoRR Mahmoud Abo Khamis, Hung Q. Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich
2017	—	`conf`	Multi-way Interacting Regression via Factorization Machines. NIPS Mikhail Yurochkin, XuanLong Nguyen, Nikolaos Vasiloglou
2017	A*	`conf`	Multilevel Clustering via Wasserstein Means. ICML Nhat Ho, XuanLong Nguyen, Mikhail Yurochkin, Hung Hai Bui, Viet Huynh, Dinh Q. Phung
2016	J	`jnl`	An ELM based predictive control method for HCCI engines. Eng. Appl. Artif. Intell. Vijay Manikandan Janakiraman, XuanLong Nguyen, Dennis Assanis
2016	—	`conf`	Geometric Dirichlet Means Algorithm for topic inference. NIPS Mikhail Yurochkin, XuanLong Nguyen
2016	J	`jnl`	On the consistency of inversion-free parameter estimation for Gaussian random fields. CoRR Hossein Keshavarz, Clayton Scott, XuanLong Nguyen
2016	J	`jnl`	On the consistency of inversion-free parameter estimation for Gaussian random fields. J. Multivar. Anal. Hossein Keshavarz, Clayton Scott, XuanLong Nguyen
2016	A	`conf`	Scalable Nonparametric Bayesian Multilevel Clustering. UAI Viet Huynh, Dinh Q. Phung, Svetha Venkatesh, XuanLong Nguyen, Matthew D. Hoffman, Hung Hai Bui
2016	J	`jnl`	Stochastic gradient based extreme learning machines for stable online learning of advanced combustion engines. Neurocomputing Vijay Manikandan Janakiraman, XuanLong Nguyen, Dennis Assanis
2015	J	`jnl`	Identification of the Dynamic Operating Envelope of HCCI Engines Using Class Imbalance Learning. IEEE Trans. Neural Networks Learn. Syst. Vijay Manikandan Janakiraman, XuanLong Nguyen, Jeff Sterniak, Dennis Assanis
2015	—	`conf`	Learning Conditional Latent Structures from Multiple Data Sources. PAKDD (1) Viet Huynh, Dinh Q. Phung, XuanLong Nguyen, Svetha Venkatesh, Hung Hai Bui
2015	J	`jnl`	Nonlinear Model Predictive Control of A Gasoline HCCI Engine Using Extreme Learning Machines. CoRR Vijay Manikandan Janakiraman, XuanLong Nguyen, Dennis Assanis
2015	J	`jnl`	Optimal change point detection in Gaussian processes. CoRR Hossein Keshavarz, Clayton Scott, XuanLong Nguyen
2015	J	`jnl`	Stochastic Gradient Based Extreme Learning Machines For Online Learning of Advanced Combustion Engines. CoRR Vijay Manikandan Janakiraman, XuanLong Nguyen, Dennis Assanis
2014	A*	`conf`	Bayesian Nonparametric Multilevel Clustering with Group-Level Contexts. ICML Tien-Vu Nguyen, Dinh Quoc Phung, XuanLong Nguyen, Svetha Venkatesh, Hung Bui
2014	J	`jnl`	Bayesian Nonparametric Multilevel Clustering with Group-Level Contexts. CoRR Vu Nguyen, Dinh Q. Phung, XuanLong Nguyen, Svetha Venkatesh, Hung Hai Bui
2014	—	`conf`	Parallel Feature Selection Inspired by Group Testing. NIPS Yingbo Zhou, Utkarsh Porwal, Ce Zhang, Hung Q. Ngo, XuanLong Nguyen, Christopher Ré, Venu Govindaraju
2014	A*	`conf`	Understanding the Limiting Factors of Topic Modeling via Posterior Contraction Analysis. ICML Jian Tang, Zhaoshi Meng, XuanLong Nguyen, Qiaozhu Mei, Ming Zhang
2013	—	`conf`	Bayesian inference as iterated random functions with applications to sequential inference in graphical models. NIPS Arash A. Amini, XuanLong Nguyen
2013	J	`jnl`	Borrowing strength in hierarchical Bayes: convergence of the Dirichlet base measure CoRR XuanLong Nguyen
2013	J	`jnl`	Modeling The Stable Operating Envelope For Partially Stable Combustion Engines Using Class Imbalance Learning. CoRR Vijay Manikandan Janakiraman, XuanLong Nguyen, Jeff Sterniak, Dennis Assanis
2013	J	`jnl`	Nonlinear identification of a gasoline HCCI engine using neural networks coupled with principal component analysis. Appl. Soft Comput. Vijay Manikandan Janakiraman, XuanLong Nguyen, Dennis Assanis
2013	J	`jnl`	Sequential Detection of Multiple Change Points in Networks: A Graphical Model Approach. IEEE Trans. Inf. Theory Arash A. Amini, XuanLong Nguyen
2012	B	`conf`	Message-passing sequential detection of multiple change points in networks. ISIT XuanLong Nguyen, Arash A. Amini, Ram Rajagopal
2012	J	`jnl`	Posterior contraction of the population polytope in finite admixture models CoRR XuanLong Nguyen
2010	J	`jnl`	Estimating Divergence Functionals and the Likelihood Ratio by Convex Risk Minimization. IEEE Trans. Inf. Theory XuanLong Nguyen, Martin J. Wainwright, Michael I. Jordan
2010	J	`jnl`	Inference of global clusters from locally distributed data. CoRR XuanLong Nguyen
2010	J	`jnl`	Simultaneous Sequential Detection of Multiple Interacting Faults CoRR Ram Rajagopal, XuanLong Nguyen, Sinem Coleri Ergen, Pravin Varaiya
2008	—	`conf`	Distributed Online Simultaneous Fault Detection for Multiple Sensors. IPSN Ram Rajagopal, XuanLong Nguyen, Sinem Coleri Ergen, Pravin Varaiya
2008	J	`jnl`	Estimating divergence functionals and the likelihood ratio by convex risk minimization CoRR XuanLong Nguyen, Martin J. Wainwright, Michael I. Jordan
2008	J	`jnl`	On Optimal Quantization Rules for Some Problems in Sequential Decentralized Detection. IEEE Trans. Inf. Theory XuanLong Nguyen, Martin J. Wainwright, Michael I. Jordan
2008	—	`conf`	Support Vector Machines, Data Reduction, and Approximate Kernel Matrices. ECML/PKDD (2) XuanLong Nguyen, Ling Huang, Anthony D. Joseph
2007	A*	`conf`	Communication-Efficient Online Detection of Network-Wide Anomalies. INFOCOM Ling Huang, XuanLong Nguyen, Minos N. Garofalakis, Joseph M. Hellerstein, Michael I. Jordan, Anthony D. Joseph, Nina Taft
2007	—	`conf`	Estimating divergence functionals and the likelihood ratio by penalized convex risk minimization. NIPS XuanLong Nguyen, Martin J. Wainwright, Michael I. Jordan
2007	B	`conf`	Nonparametric estimation of the likelihood ratio and divergence functionals. ISIT XuanLong Nguyen, Martin J. Wainwright, Michael I. Jordan
2006	—	`conf`	In-Network PCA and Anomaly Detection. NIPS Ling Huang, XuanLong Nguyen, Minos N. Garofalakis, Michael I. Jordan, Anthony D. Joseph, Nina Taft
2006	B	`conf`	On optimal quantization rules for sequential decision problems. ISIT XuanLong Nguyen, Martin J. Wainwright, Michael I. Jordan
2006	J	`jnl`	On optimal quantization rules for some sequential decision problems CoRR XuanLong Nguyen, Martin J. Wainwright, Michael I. Jordan
2005	J	`jnl`	A kernel-based learning approach to ad hoc sensor network localization. ACM Trans. Sens. Networks XuanLong Nguyen, Michael I. Jordan, Bruno Sinopoli
2005	—	`conf`	Divergences, surrogate loss functions and experimental design. NIPS XuanLong Nguyen, Martin J. Wainwright, Michael I. Jordan
2005	J	`jnl`	Nonparametric decentralized detection using kernel methods. IEEE Trans. Signal Process. XuanLong Nguyen, Martin J. Wainwright, Michael I. Jordan
2005	J	`jnl`	On divergences, surrogate loss functions, and decentralized detection CoRR XuanLong Nguyen, Martin J. Wainwright, Michael I. Jordan
2004	A*	`conf`	Decentralized detection and classification using kernel methods. ICML XuanLong Nguyen, Martin J. Wainwright, Michael I. Jordan
2003	—	`conf`	On the Concentration of Expectation and Approximate Inference in Layered Networks. NIPS XuanLong Nguyen, Michael I. Jordan
2002	J	`jnl`	Planning graph as the basis for deriving heuristics for plan synthesis by state space and CSP search. Artif. Intell. XuanLong Nguyen, Subbarao Kambhampati, Romeo Sanchez Nigenda
2001	A*	`conf`	Reviving Partial Order Planning. IJCAI XuanLong Nguyen, Subbarao Kambhampati
2000	—	`conf`	Extracting Effective and Admissible State Space Heuristics from the Planning Graph. AAAI/IAAI XuanLong Nguyen, Subbarao Kambhampati