Nguyen, XuanLong

28 publications

ICLR 2026 Structured Flow Autoencoders: Learning Structured Probabilistic Representations with Flow Matching Yidan Xu, Yixin Wang, XuanLong Nguyen

JMLR 2024 Functional Optimal Transport: Regularized mAP Estimation and Domain Adaptation for Functional Data Jiacheng Zhu, Aritra Guha, Dat Do, Mengdi Xu, XuanLong Nguyen, Ding Zhao

ICML 2023 Interpolation for Robust Learning: Data Augmentation on Wasserstein Geodesics Jiacheng Zhu, Jielin Qiu, Aritra Guha, Zhuolin Yang, Xuanlong Nguyen, Bo Li, Ding Zhao

ICML 2023 On Excess Mass Behavior in Gaussian Mixture Models with Orlicz-Wasserstein Distances Aritra Guha, Nhat Ho, Xuanlong Nguyen

UAI 2023 Scalable Nonparametric Bayesian Learning for Dynamic Velocity Fields Sunrit Chakraborty, Aritra Guha, Rayleigh Lei, XuanLong Nguyen

NeurIPS 2022 Beyond Black Box Densities: Parameter Learning for the Deviated Components Dat Do, Nhat Ho, Xuanlong Nguyen

CHIL 2022 PhysioMTL: Personalizing Physiological Patterns Using Optimal Transport Multi-Task Regression Jiacheng Zhu, Gregory Darnell, Agni Kumar, Ding Zhao, Bo Li, Xuanlong Nguyen, Shirley You Ren

JMLR 2021 On Efficient Multilevel Clustering via Wasserstein Distances Viet Huynh, Nhat Ho, Nhan Dam, XuanLong Nguyen, Mikhail Yurochkin, Hung Bui, Dinh Phung

AISTATS 2020 Rk-Means: Fast Clustering for Relational Data Ryan Curtin, Benjamin Moseley, Hung Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich

ICML 2019 Dirichlet Simplex Nest and Geometric Inference Mikhail Yurochkin, Aritra Guha, Yuekai Sun, Xuanlong Nguyen

NeurIPS 2019 Scalable Inference of Topic Evolution via Models for Latent Geometric Structures Mikhail Yurochkin, Zhiwei Fan, Aritra Guha, Paraschos Koutris, Xuanlong Nguyen

NeurIPS 2017 Conic Scan-and-Cover Algorithms for Nonparametric Topic Modeling Mikhail Yurochkin, Aritra Guha, Xuanlong Nguyen

NeurIPS 2017 Multi-Way Interacting Regression via Factorization Machines Mikhail Yurochkin, Xuanlong Nguyen, Nikolaos Vasiloglou

ICML 2017 Multilevel Clustering via Wasserstein Means Nhat Ho, XuanLong Nguyen, Mikhail Yurochkin, Hung Hai Bui, Viet Huynh, Dinh Phung

NeurIPS 2016 Geometric Dirichlet Means Algorithm for Topic Inference Mikhail Yurochkin, Xuanlong Nguyen

UAI 2016 Scalable Nonparametric Bayesian Multilevel Clustering Viet Huynh, Dinh Q. Phung, Svetha Venkatesh, XuanLong Nguyen, Matthew D. Hoffman, Hung Hai Bui

ICML 2014 Bayesian Nonparametric Multilevel Clustering with Group-Level Contexts Tien Vu Nguyen, Dinh Phung, Xuanlong Nguyen, Swetha Venkatesh, Hung Bui

NeurIPS 2014 Parallel Feature Selection Inspired by Group Testing Yingbo Zhou, Utkarsh Porwal, Ce Zhang, Hung Q Ngo, Xuanlong Nguyen, Christopher Ré, Venu Govindaraju

ICML 2014 Understanding the Limiting Factors of Topic Modeling via Posterior Contraction Analysis Jian Tang, Zhaoshi Meng, Xuanlong Nguyen, Qiaozhu Mei, Ming Zhang

NeurIPS 2013 Bayesian Inference as Iterated Random Functions with Applications to Sequential Inference in Graphical Models Arash Amini, Xuanlong Nguyen

ECML-PKDD 2008 Support Vector Machines, Data Reduction, and Approximate Kernel Matrices XuanLong Nguyen, Ling Huang, Anthony D. Joseph

NeurIPS 2007 Estimating Divergence Functionals and the Likelihood Ratio by Penalized Convex Risk Minimization Xuanlong Nguyen, Martin J. Wainwright, Michael I. Jordan

NeurIPS 2006 In-Network PCA and Anomaly Detection Ling Huang, Xuanlong Nguyen, Minos Garofalakis, Michael I. Jordan, Anthony Joseph, Nina Taft

NeurIPS 2005 Divergences, Surrogate Loss Functions and Experimental Design Xuanlong Nguyen, Martin J. Wainwright, Michael I. Jordan

ICML 2004 Decentralized Detection and Classification Using Kernel Methods XuanLong Nguyen, Martin J. Wainwright, Michael I. Jordan

NeurIPS 2003 On the Concentration of Expectation and Approximate Inference in Layered Networks Xuanlong Nguyen, Michael I. Jordan

IJCAI 2001 Reviving Partial Order Planning XuanLong Nguyen, Subbarao Kambhampati

AAAI 2000 Extracting Effective and Admissible State Space Heuristics from the Planning Graph XuanLong Nguyen, Subbarao Kambhampati