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Quantized Training of Gradient Boosting Decision Trees


Jul 20, 2022
Yu Shi, Guolin Ke, Zhuoming Chen, Shuxin Zheng, Tie-Yan Liu


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METRO: Efficient Denoising Pretraining of Large Scale Autoencoding Language Models with Model Generated Signals


Apr 16, 2022
Payal Bajaj, Chenyan Xiong, Guolin Ke, Xiaodong Liu, Di He, Saurabh Tiwary, Tie-Yan Liu, Paul Bennett, Xia Song, Jianfeng Gao

* Update details in scaled initialization and add acknowledgement 

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An Empirical Study of Graphormer on Large-Scale Molecular Modeling Datasets


Mar 14, 2022
Yu Shi, Shuxin Zheng, Guolin Ke, Yifei Shen, Jiacheng You, Jiyan He, Shengjie Luo, Chang Liu, Di He, Tie-Yan Liu

* Wrong dual-submission (arXiv:2203.04810) with negligently 

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Benchmarking Graphormer on Large-Scale Molecular Modeling Datasets


Mar 09, 2022
Yu Shi, Shuxin Zheng, Guolin Ke, Yifei Shen, Jiacheng You, Jiyan He, Shengjie Luo, Chang Liu, Di He, Tie-Yan Liu


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Stable, Fast and Accurate: Kernelized Attention with Relative Positional Encoding


Jun 23, 2021
Shengjie Luo, Shanda Li, Tianle Cai, Di He, Dinglan Peng, Shuxin Zheng, Guolin Ke, Liwei Wang, Tie-Yan Liu

* Preprint. Work in Progress 

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First Place Solution of KDD Cup 2021 & OGB Large-Scale Challenge Graph Prediction Track


Jun 20, 2021
Chengxuan Ying, Mingqi Yang, Shuxin Zheng, Guolin Ke, Shengjie Luo, Tianle Cai, Chenglin Wu, Yuxin Wang, Yanming Shen, Di He


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Do Transformers Really Perform Bad for Graph Representation?


Jun 17, 2021
Chengxuan Ying, Tianle Cai, Shengjie Luo, Shuxin Zheng, Guolin Ke, Di He, Yanming Shen, Tie-Yan Liu


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Deep Subdomain Adaptation Network for Image Classification


Jun 17, 2021
Yongchun Zhu, Fuzhen Zhuang, Jindong Wang, Guolin Ke, Jingwu Chen, Jiang Bian, Hui Xiong, Qing He

* published on TNNLS 

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