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BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximation


Jun 21, 2021
Mingguo He, Zhewei Wei, Zengfeng Huang, Hongteng Xu

* 14 pages, 31 figures 

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Learning Graphon Autoencoders for Generative Graph Modeling


May 29, 2021
Hongteng Xu, Peilin Zhao, Junzhou Huang, Dixin Luo


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Hawkes Processes on Graphons


Feb 04, 2021
Hongteng Xu, Dixin Luo, Hongyuan Zha


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Learning Graphons via Structured Gromov-Wasserstein Barycenters


Dec 17, 2020
Hongteng Xu, Dixin Luo, Lawrence Carin, Hongyuan Zha

* AAAI 2021 

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A Hypergradient Approach to Robust Regression without Correspondence


Nov 30, 2020
Yujia Xie, Yixiu Mao, Simiao Zuo, Hongteng Xu, Xiaojing Ye, Tuo Zhao, Hongyuan Zha


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Hierarchical Optimal Transport for Robust Multi-View Learning


Jun 08, 2020
Dixin Luo, Hongteng Xu, Lawrence Carin


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Learning Autoencoders with Relational Regularization


Feb 27, 2020
Hongteng Xu, Dixin Luo, Ricardo Henao, Svati Shah, Lawrence Carin


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Quaternion Product Units for Deep Learning on 3D Rotation Groups


Dec 17, 2019
Xuan Zhang, Shaofei Qin, Yi Xu, Hongteng Xu


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Graph-Driven Generative Models for Heterogeneous Multi-Task Learning


Nov 20, 2019
Wenlin Wang, Hongteng Xu, Zhe Gan, Bai Li, Guoyin Wang, Liqun Chen, Qian Yang, Wenqi Wang, Lawrence Carin

* Accepted by AAAI-2020 

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Gromov-Wasserstein Factorization Models for Graph Clustering


Nov 19, 2019
Hongteng Xu

* The Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20) 

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Collaborative Filtering with A Synthetic Feedback Loop


Oct 21, 2019
Wenlin Wang, Hongteng Xu, Ruiyi Zhang, Wenqi Wang, Lawrence Carin


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An Optimal Transport Framework for Zero-Shot Learning


Oct 20, 2019
Wenlin Wang, Hongteng Xu, Guoyin Wang, Wenqi Wang, Lawrence Carin


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Fused Gromov-Wasserstein Alignment for Hawkes Processes


Oct 04, 2019
Dixin Luo, Hongteng Xu, Lawrence Carin

* The workshop on learning with temporal point processes in NeurIPS 2019 (WTPP19) 

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Adversarial Self-Paced Learning for Mixture Models of Hawkes Processes


Jun 20, 2019
Dixin Luo, Hongteng Xu, Lawrence Carin


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Interpretable ICD Code Embeddings with Self- and Mutual-Attention Mechanisms


Jun 13, 2019
Dixin Luo, Hongteng Xu, Lawrence Carin


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Scalable Gromov-Wasserstein Learning for Graph Partitioning and Matching


May 22, 2019
Hongteng Xu, Dixin Luo, Lawrence Carin


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Topic-Guided Variational Autoencoders for Text Generation


Mar 17, 2019
Wenlin Wang, Zhe Gan, Hongteng Xu, Ruiyi Zhang, Guoyin Wang, Dinghan Shen, Changyou Chen, Lawrence Carin


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Quaternion Convolutional Neural Networks


Mar 02, 2019
Xuanyu Zhu, Yi Xu, Hongteng Xu, Changjian Chen


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Gromov-Wasserstein Learning for Graph Matching and Node Embedding


Jan 17, 2019
Hongteng Xu, Dixin Luo, Hongyuan Zha, Lawrence Carin


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PoPPy: A Point Process Toolbox Based on PyTorch


Oct 25, 2018
Hongteng Xu


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Distilled Wasserstein Learning for Word Embedding and Topic Modeling


Sep 12, 2018
Hongteng Xu, Wenlin Wang, Wei Liu, Lawrence Carin


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Predicting Smoking Events with a Time-Varying Semi-Parametric Hawkes Process Model


Sep 05, 2018
Matthew Engelhard, Hongteng Xu, Lawrence Carin, Jason A Oliver, Matthew Hallyburton, F Joseph McClernon

* Presented at Machine Learning for Healthcare 2018, Stanford, CA 

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A unified framework for manifold landmarking


Sep 02, 2018
Hongteng Xu, Licheng Yu, Mark Davenport, Hongyuan Zha


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Flexible Network Binarization with Layer-wise Priority


Feb 16, 2018
Lixue Zhuang, Yi Xu, Bingbing Ni, Hongteng Xu

* More experiments on image classification are planned 

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Superposition-Assisted Stochastic Optimization for Hawkes Processes


Feb 14, 2018
Hongteng Xu, Xu Chen, Lawrence Carin


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Benefits from Superposed Hawkes Processes


Feb 14, 2018
Hongteng Xu, Dixin Luo, Xu Chen, Lawrence Carin

* AISTATS 2018 

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