个人简历

教育经历\r
2013年8月至2017年5月：佐治亚理工学院，博士\r
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\r
2006年9月至2010年7月：天津大学，学士\r
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工作经历\r
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\r
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\r
2017年8月至2017年12月，杜克大学，博士后研究员

研究领域

"""""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\r
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\r
网络分析与控制：无限图模型、社交网络建模\r
点过程模型：霍克斯过程、事件序列分析"

近期论文

Gromov-Wasserstein Factorization Models for Graph Clustering Hongteng Xu AAAI Conference on Artificial Intelligence (AAAI), 2020.\r
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Learning Autoencoders with Relational Regularization Hongteng Xu, Dixin Luo, Ricardo Henao, Svati Shah, Lawrence Carin The International Conference on Machine Learning (ICML), 2020.\r
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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.\r
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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.\r
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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.\r
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Learning Registered Point Processes from Idiosyncratic Observations, Hongteng Xu, Lawrence Carin, Hongyuan Zha The International Conference on Machine Learning (ICML), 2018.\r
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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.\r
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A Unified Framework for Manifold Landmarking Hongteng Xu, Licheng Yu, Mark Davenport, Hongyuan Zha IEEE Transactions on Signal Processing (TSP), 2018.\r
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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.\r
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Learning Hawkes Processes from Short Doubly-Censored Event Sequences, Hongteng Xu, Dixin Luo, Hongyuan Zha International Conference on Machine Learning (ICML), 2017.\r
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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.\r
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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.\r
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Learning Granger Causality for Hawkes Processes, Hongteng Xu, Mehrdad Farajtabar and Hongyuan Zha International Conference on Machine Learning (ICML), 2016.\r
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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.\r
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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.\r
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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.\r
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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.\r
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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.\r
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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.\r
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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.\r
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Generalized Equalization Model for Image Enhancement, Hongteng Xu, Guangtao Zhai, Xiaolin Wu, Xiaokang Yang IEEE Transactions on Multimedia (TMM), 2014.\r
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Manifold based Image Synthesis from Sparse Samples, Hongteng Xu, Hongyuan Zha IEEE Conference on Computer Vision (ICCV), 2013.\r
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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.