许洪腾 - 中国人民大学 - 高瓴人工智能学院

个人简介

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

近期论文

查看导师最新文章（温馨提示：请注意重名现象，建议点开原文通过作者单位确认）

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. 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. 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. 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. 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. 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. 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. 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.