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DeepGAR: Deep Graph Learning for Analogical Reasoning


Nov 19, 2022
Chen Ling, Tanmoy Chowdhury, Junji Jiang, Junxiang Wang, Xuchao Zhang, Haifeng Chen, Liang Zhao

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* 22nd IEEE International Conference on Data Mining (ICDM 2022) 

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Source Localization of Graph Diffusion via Variational Autoencoders for Graph Inverse Problems


Jun 24, 2022
Chen Ling, Junji Jiang, Junxiang Wang, Liang Zhao

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* 11 pages, accepted by SIGKDD 2022 

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An Invertible Graph Diffusion Neural Network for Source Localization


Jun 18, 2022
Junxiang Wang, Junji Jiang, Liang Zhao

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* WWW 2022 

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Do Multi-Lingual Pre-trained Language Models Reveal Consistent Token Attributions in Different Languages?


Dec 23, 2021
Junxiang Wang, Xuchao Zhang, Bo Zong, Yanchi Liu, Wei Cheng, Jingchao Ni, Haifeng Chen, Liang Zhao

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A Convergent ADMM Framework for Efficient Neural Network Training


Dec 22, 2021
Junxiang Wang, Hongyi Li, Liang Zhao

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* This work is in progress, a journal extension of the conference paper: arXiv:1905.13611 

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Community-based Layerwise Distributed Training of Graph Convolutional Networks


Dec 17, 2021
Hongyi Li, Junxiang Wang, Yongchao Wang, Yue Cheng, Liang Zhao

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* accepted by NeurIPS 2021 OPT workshop 

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Towards Quantized Model Parallelism for Graph-Augmented MLPs Based on Gradient-Free ADMM framework


May 20, 2021
Junxiang Wang, Hongyi Li, Zheng Chai, Yongchao Wang, Yue Cheng, Liang Zhao

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* Junxiang Wang and Hongyi Li contribute equally to this work, and Yongchao Wang and Liang Zhao are corresponding authors. This work is under progress. arXiv admin note: substantial text overlap with arXiv:2009.02868 

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Sign-regularized Multi-task Learning


Feb 22, 2021
Johnny Torres, Guangji Bai, Junxiang Wang, Liang Zhao, Carmen Vaca, Cristina Abad

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* 17 pages, 4 figures, v1 

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Tunable Subnetwork Splitting for Model-parallelism of Neural Network Training


Sep 16, 2020
Junxiang Wang, Zheng Chai, Yue Cheng, Liang Zhao

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* ICML 2020 Workshop on "Beyond first-order methods in ML systems" 

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