FACULTY & RESEARCH

Hongteng Xu
Tenure-track Associate Professor
Dr. Hongteng Xu got his Ph.D. from the School of Electrical and Computer Engineering, Georgia Institute of Technology, in 2017. Before that, he earned his Master's and Bachelor's degrees from Shanghai Jiao Tong University in 2013 and Tianjin University in 2010. His research interests include machine learning and its applications, especially the theory of optimal transport and point process models for complex data analysis, modeling, prediction, generation, and control. He has published over 20 papers at top-tier conferences and journals in the field of machine learning.

Personal Homepage: https://hongtengxu.github.io

Detailed Information

Education

PhD:Georgia Institute of Technology,August 2013 to May 2017

Dual-MS:GeorgiaTech-SJTU,August 2010 to May 2013

BS:Tianjin University,September 2006 to July 2010

Professional Experience

Tenure-track Associate Professor: Gaoling School of Artificial Intelligence, Renmin University of China, December 2020 to present

Infinia ML Inc., Senior research scientist; Duke University, Visiting researcher,January 2018 to September 2020

Research Interests

Optimal transport and its application: metric learning, graph analysis and generation, learning for matching and ranking

Point process models: Hawkes process, Markov chain, event sequence analysis

Network analysis and control: Graphon model, social network modeling, network simulation and optimization

Deep learning: Non-real neural networks, high-dimensional dataanalysis and synthesis

Publications

(一)Journal

Hongteng Xu, Licheng Yu, Mark Davenport, Hongyuan Zha - "A Unified Framework for Manifold Landmarking", IEEE Transactions on Signal Processing (TSP), 2018.

Hongteng Xu, Weichang Wu, Shamim Nemati, Hongyuan Zha - "Patient Flow Prediction via Discriminative Learning of Mutually-Correcting Processes", IEEE Transactions on Knowledge and Data Engineering (TKDE), 2017.

Dixin Luo, Hongteng Xu, Yi Zhen, et al. - "Learning Mixtures of Markov Chains from Aggregate Data with Structural Constraints," IEEE Transactions on Knowledge and Data Engineering (TKDE), 2016.

Hongteng Xu, Guangtao Zhai, Xiaolin Wu, Xiaokang Yang - "Generalized Equalization Model for Image Enhancement," IEEE Transactions on Multimedia (TMM), 2014.

Hongteng Xu, Guangtao Zhai, Xiaokang Yang - "Single Image Super-resolution with Detail Enhancement based on Local Fractal Analysis of Gradient," IEEE Transactions on Circuit Systems for Video Technology (CSVT), 2013.

(二)Conference

Hongteng Xu, Dixin Luo, Ricardo Henao, Svati Shah, Lawrence Carin - "Learning Autoencoders with Relational Regularization", The International Conference on Machine Learning (ICML), 2020.

Hongteng Xu - "Gromov-Wasserstein Factorization Models for Graph Clustering", AAAI Conference on Artificial Intelligence (AAAI), 2020.

Hongteng Xu, Dixin Luo, Lawrence Carin - "Scalable Gromov-Wasserstein Learning for Graph Partitioning and Matching", The Conference on Neural Information and Processing System (NeurIPS), 2019.

Hongteng Xu, Dixin Luo, Hongyuan Zha, Lawrence Carin - "Gromov-Wasserstein Learning for Graph Matching and Node Embedding", The International Conference on Machine Learning (ICML), 2019.

Hongteng Xu, Wenlin Wang, Wei Liu, Lawrence Carin - "Distilled Wasserstein Learning for Word Embedding and Topic Modeling", The Conference on Neural Information and Processing System (NeurIPS), 2018.

Hongteng Xu, Lawrence Carin, Hongyuan Zha - "Learning Registered Point Processes from Idiosyncratic Observations," The International Conference on Machine Learning (ICML), 2018.

Hongteng Xu, Dixin Luo, Lawrence Carin - "Online Continuous-Time Tensor Factorization Based on Pairwise Interactive Point Processes," The International Joint Conference on Artificial Intelligence (IJCAI-ECAI), 2018.

Hongteng Xu and Hongyuan Zha - "A Dirichlet Mixture Model of Hawkes Processes for Event Sequence Clustering" Annual Conference on Neural Information Processing Systems (NeurIPS), 2017.

Hongteng Xu, Dixin Luo, Hongyuan Zha - "Learning Hawkes Processes from Short Doubly-Censored Event Sequences," International Conference on Machine Learning (ICML), 2017.

Hongteng Xu, Junchi Yan, Nils Persson, Weiyao Lin and Hongyuan Zha - "Fractal Dimension Invariant Filtering and Its CNN-based Implementation," IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2017.

Hongteng Xu, Mehrdad Farajtabar and Hongyuan Zha - "Learning Granger Causality for Hawkes Processes," International Conference on Machine Learning (ICML), 2016.

Hongteng Xu, Yang Zhou, Weiyao Lin and Hongyuan Zha - "Unsupervised Trajectory Clustering via Adaptive Multi-Kernel-based Shrinkage," International Conference on Computer Vision (ICCV), 2015.

Hongteng Xu, Yi Zhen, Hongyuan Zha - "Trailer Generation via A Point Process-based Visual Attractiveness Model," The Twenty-fourth International Joint Conference on Artificial Intelligence (IJCAI), 2015.

Hongteng Xu, Dixin Luo, Yi Zhen, Xia Ning, Hongyuan Zha, et al. - "Multi-task Multi-dimensional Hawkes Processes for Modeling Event Sequences," The Twenty-fourth International Joint Conference on Artificial Intelligence (IJCAI), 2015.

Hongteng Xu, Hongyuan Zha, Ren-Cang Li, Mark A. Davenport - "Active Manifold Learning via Gershgorin Circle Guided Sample Selection," The Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI), 2015.

Hongteng Xu, Licheng Yu, Dixin Luo, Hongyuan Zha, Yi Xu - "Dictionary Learning with Mutually Reinforcing Group-Graph Structures," The Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI), 2015.

Hongteng Xu, Hongyuan Zha, Mark A. Davenport - "Manifold Based Dynamic Texture Synthesis from Extremely Few Samples," IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2014.

Hongteng Xu, Hongyuan Zha - "Manifold based Image Synthesis from Sparse Samples," IEEE Conference on Computer Vision (ICCV), 2013.

Services

Guest Editor:TNNLS

Reviewer:TPAMI、TKDE、TIP、TCSVT、TMM、TSP

Tutorial:KDD2019

Area Chair:ICML2020、ICLR2021、AAAI2021

Reviewer:ICML2018-2019、NeurIPS2018-2019、AAAI2017-2020、CVPR2018-2020

Awards

Coulter Fellowship, Georgia Institute of Technology, 2010


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