教育经历

  • 2013年8月至2017年5月:佐治亚理工学院,博士
  • 2010年8月至2013年5月:佐治亚理工-上海交通大学双硕士项目,硕士
  • 2006年9月至2010年7月:天津大学,学士

工作经历

  • 2020年12月 - 至今,中国人民大学高瓴人工智能学院,准聘副教授
  • 2018年1月至2020年9月,Infinia ML Inc.,高级研究员,兼任杜克大学客座研究员
  • 2017年8月至2017年12月,杜克大学,博士后研究员

研究方向

最优传输理论及应用:度量学习、图分析模型、图生成模型、基于学习的组合优化近似求解

深度学习:非实数神经网络模型、高维数据分析与合成、隐式神经网络设计与学习、无监督学习

网络分析与控制:无限图模型、社交网络建模

点过程模型:霍克斯过程、事件序列分析

学生要求

对科研具有主观能动性;有较好的数学基础和编程能力;乐于交流和团队协作。

教授课程

  • 现代数值方法:2021秋,2022秋
  • 智慧医疗:2021秋
  • 智慧医药与公共卫生:2022秋
  • 机器学习基础:2022春

学术论文

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

荣誉奖励

  • 佐治亚理工学院Coulter Fellowship,2010年
  • 上海市研究生优秀学术成果(学位论文),2014年

社会兼职

  • 期刊Guest Editor:TNNLS
  • 期刊Reviewer:TPAMI、TKDE、TIP、TCSVT、TMM、TSP等
  • 会议Tutorial:KDD2019、AAAI2022
  • 会议Area Chair:ICML2020、ICLR2021、AAAI2021、ICLR2023等
  • 会议Reviewer:ICML2018-2022、NeurIPS2018-2022、AAAI2017-2022、CVPR2018-2020等

contact

电话:--

邮箱:hongtengxu@ruc.edu.cn

个人网页:https://hongtengxu.github.io

办公地址:--