详细资料

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、基于学习的匹配与排序

点过程模型：霍克斯过程、马尔科夫链、事件序列分析

网络分析与控制：无限图模型、社交网络建模、网络仿真与优化

深度学习：非实数神经网络模型、高维数据分析与合成

对学生的培养要求

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。

科研成果

1、代表性期刊论文

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.

2、代表性会议论文

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.

社会兼职

期刊Guest Editor：TNNLS

期刊Reviewer：TPAMI、TKDE、TIP、TCSVT、TMM、TSP等等

会议Tutorial：KDD2019

会议Area Chair：ICML2020、ICLR2021、AAAI2021等等

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

荣誉获奖

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