{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T21:47:00Z","timestamp":1730324820000,"version":"3.28.0"},"publisher-location":"New York, NY, USA","reference-count":68,"publisher":"ACM","funder":[{"name":"NSFC","award":["61832001, 61972004"]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,4,25]]},"DOI":"10.1145\/3485447.3511986","type":"proceedings-article","created":{"date-parts":[[2022,4,25]],"date-time":"2022-04-25T01:13:07Z","timestamp":1650849187000},"page":"1817-1828","update-policy":"http:\/\/dx.doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":26,"title":["PaSca: A Graph Neural Architecture Search System under the Scalable Paradigm"],"prefix":"10.1145","author":[{"given":"Wentao","family":"Zhang","sequence":"first","affiliation":[{"name":"School of CS & Key Lab of High Confidence Software Technologies, Peking University, China and Tencent Inc., China"}]},{"given":"Yu","family":"Shen","sequence":"additional","affiliation":[{"name":"School of CS & Key Lab of High Confidence Software Technologies, Peking University, China"}]},{"given":"Zheyu","family":"Lin","sequence":"additional","affiliation":[{"name":"School of CS & Key Lab of High Confidence Software Technologies, Peking University, China"}]},{"given":"Yang","family":"Li","sequence":"additional","affiliation":[{"name":"School of CS & Key Lab of High Confidence Software Technologies, Peking University, China"}]},{"given":"Xiaosen","family":"Li","sequence":"additional","affiliation":[{"name":"Tencent Inc., China"}]},{"given":"Wen","family":"Ouyang","sequence":"additional","affiliation":[{"name":"Tencent Inc., China"}]},{"given":"Yangyu","family":"Tao","sequence":"additional","affiliation":[{"name":"Tencent Inc., China"}]},{"given":"Zhi","family":"Yang","sequence":"additional","affiliation":[{"name":"School of CS & Key Lab of High Confidence Software Technologies, Peking University, China"}]},{"given":"Bin","family":"Cui","sequence":"additional","affiliation":[{"name":"School of CS & Key Lab of High Confidence Software Technologies, Peking University, China and Institute of Computational Social Science, Peking University (Qingdao), China"}]}],"member":"320","published-online":{"date-parts":[[2022,4,25]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3449917"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2017.2693418"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5731"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00659"},{"volume-title":"International Conference on Learning Representations.","year":"2018","author":"Chen Jie","key":"e_1_3_2_1_5_1","unstructured":"Jie Chen , Tengfei Ma , and Cao Xiao . 2018 . FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling . In International Conference on Learning Representations. Jie Chen, Tengfei Ma, and Cao Xiao. 2018. FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling. In International Conference on Learning Representations."},{"volume-title":"Scalable graph neural networks via bidirectional propagation. Advances in neural information processing systems 33","year":"2020","author":"Chen Ming","key":"e_1_3_2_1_6_1","unstructured":"Ming Chen , Zhewei Wei , Bolin Ding , Yaliang Li , Ye Yuan , Xiaoyong Du , and Ji-Rong Wen . 2020. Scalable graph neural networks via bidirectional propagation. Advances in neural information processing systems 33 ( 2020 ), 14556\u201314566. Ming Chen, Zhewei Wei, Bolin Ding, Yaliang Li, Ye Yuan, Xiaoyong Du, and Ji-Rong Wen. 2020. Scalable graph neural networks via bidirectional propagation. Advances in neural information processing systems 33 (2020), 14556\u201314566."},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330925"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3449927"},{"volume-title":"Single-and multi-objective evolutionary design optimization assisted by gaussian random field metamodels","author":"Emmerich Michael","key":"e_1_3_2_1_9_1","unstructured":"Michael Emmerich . 2005. Single-and multi-objective evolutionary design optimization assisted by gaussian random field metamodels . University of Dormund(2005) . Michael Emmerich. 2005. Single-and multi-objective evolutionary design optimization assisted by gaussian random field metamodels. University of Dormund(2005)."},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/3357384.3357979"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11432-020-3112-8"},{"volume-title":"SIGN: Scalable Inception Graph Neural Networks. In ICML 2020 Workshop on Graph Representation Learning and Beyond.","year":"2020","author":"Frasca Fabrizio","key":"e_1_3_2_1_12_1","unstructured":"Fabrizio Frasca , Emanuele Rossi , Davide Eynard , Benjamin Chamberlain , Michael Bronstein , and Federico Monti . 2020 . SIGN: Scalable Inception Graph Neural Networks. In ICML 2020 Workshop on Graph Representation Learning and Beyond. Fabrizio Frasca, Emanuele Rossi, Davide Eynard, Benjamin Chamberlain, Michael Bronstein, and Federico Monti. 2020. SIGN: Scalable Inception Graph Neural Networks. In ICML 2020 Workshop on Graph Representation Learning and Beyond."},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2020\/195"},{"volume-title":"Syntax-guided text generation via graph neural network. Sci. China Inf. Sci. 64, 5","year":"2021","author":"Guo Qipeng","key":"e_1_3_2_1_14_1","unstructured":"Qipeng Guo , Xipeng Qiu , Xiangyang Xue , and Zheng Zhang . 2021. Syntax-guided text generation via graph neural network. Sci. China Inf. Sci. 64, 5 ( 2021 ). Qipeng Guo, Xipeng Qiu, Xiangyang Xue, and Zheng Zhang. 2021. Syntax-guided text generation via graph neural network. Sci. China Inf. Sci. 64, 5 (2021)."},{"volume-title":"Inductive representation learning on large graphs. Advances in neural information processing systems 30","year":"2017","author":"Hamilton Will","key":"e_1_3_2_1_15_1","unstructured":"Will Hamilton , Zhitao Ying , and Jure Leskovec . 2017. Inductive representation learning on large graphs. Advances in neural information processing systems 30 ( 2017 ). Will Hamilton, Zhitao Ying, and Jure Leskovec. 2017. Inductive representation learning on large graphs. Advances in neural information processing systems 30 (2017)."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2020.106622"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3449957"},{"volume-title":"Open graph benchmark: Datasets for machine learning on graphs. Advances in neural information processing systems 33","year":"2020","author":"Hu Weihua","key":"e_1_3_2_1_18_1","unstructured":"Weihua Hu , Matthias Fey , Marinka Zitnik , Yuxiao Dong , Hongyu Ren , Bowen Liu , Michele Catasta , and Jure Leskovec . 2020. Open graph benchmark: Datasets for machine learning on graphs. Advances in neural information processing systems 33 ( 2020 ), 22118\u201322133. Weihua Hu, Matthias Fey, Marinka Zitnik, Yuxiao Dong, Hongyu Ren, Bowen Liu, Michele Catasta, and Jure Leskovec. 2020. Open graph benchmark: Datasets for machine learning on graphs. Advances in neural information processing systems 33 (2020), 22118\u201322133."},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/3447786.3456244"},{"volume-title":"Semi-Supervised Classification with Graph Convolutional Networks. In International Conference on Learning Representations.","year":"2017","author":"Kipf N","key":"e_1_3_2_1_20_1","unstructured":"Thomas\u00a0 N Kipf and Max Welling . 2017 . Semi-Supervised Classification with Graph Convolutional Networks. In International Conference on Learning Representations. Thomas\u00a0N Kipf and Max Welling. 2017. Semi-Supervised Classification with Graph Convolutional Networks. In International Conference on Learning Representations."},{"volume-title":"International Conference on Learning Representations.","year":"2019","author":"Klicpera Johannes","key":"e_1_3_2_1_21_1","unstructured":"Johannes Klicpera , Aleksandar Bojchevski , and Stephan G\u00fcnnemann . 2019 . Predict then Propagate: Graph Neural Networks meet Personalized PageRank . In International Conference on Learning Representations. Johannes Klicpera, Aleksandar Bojchevski, and Stephan G\u00fcnnemann. 2019. Predict then Propagate: Graph Neural Networks meet Personalized PageRank. In International Conference on Learning Representations."},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/3357384.3357820"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11604"},{"volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence, Vol.\u00a035","year":"2021","author":"Li Yang","key":"e_1_3_2_1_24_1","unstructured":"Yang Li , Yu Shen , Jiawei Jiang , Jinyang Gao , Ce Zhang , and Bin Cui . 2021 . MFES-HB: Efficient Hyperband with Multi-Fidelity Quality Measurements . In Proceedings of the AAAI Conference on Artificial Intelligence, Vol.\u00a035 . AAAI Press, 8491\u20138500. Yang Li, Yu Shen, Jiawei Jiang, Jinyang Gao, Ce Zhang, and Bin Cui. 2021. MFES-HB: Efficient Hyperband with Multi-Fidelity Quality Measurements. In Proceedings of the AAAI Conference on Artificial Intelligence, Vol.\u00a035. AAAI Press, 8491\u20138500."},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/3447548.3467061"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.14778\/3476249.3476270"},{"volume-title":"Proc. AAAI Conf. Artif. Intell, Vol.\u00a035","year":"2021","author":"Li Yanxi","key":"e_1_3_2_1_27_1","unstructured":"Yanxi Li , Zean Wen , Yunhe Wang , and Chang Xu . 2021 . One-shot graph neural architecture search with dynamic search space . In Proc. AAAI Conf. Artif. Intell, Vol.\u00a035 . 8510\u20138517. Yanxi Li, Zean Wen, Yunhe Wang, and Chang Xu. 2021. One-shot graph neural architecture search with dynamic search space. In Proc. AAAI Conf. Artif. Intell, Vol.\u00a035. 8510\u20138517."},{"volume-title":"Graph Partition Neural Networks for Semi-Supervised Classification. In International Conference on Learning Representations.","year":"2018","author":"Liao Renjie","key":"e_1_3_2_1_28_1","unstructured":"Renjie Liao , Marc Brockschmidt , Daniel Tarlow , Alexander Gaunt , Raquel Urtasun , and Richard Zemel . 2018 . Graph Partition Neural Networks for Semi-Supervised Classification. In International Conference on Learning Representations. Renjie Liao, Marc Brockschmidt, Daniel Tarlow, Alexander Gaunt, Raquel Urtasun, and Richard Zemel. 2018. Graph Partition Neural Networks for Semi-Supervised Classification. In International Conference on Learning Representations."},{"volume-title":"DARTS: Differentiable Architecture Search. In International Conference on Learning Representations.","year":"2019","author":"Liu Hanxiao","key":"e_1_3_2_1_29_1","unstructured":"Hanxiao Liu , Karen Simonyan , and Yiming Yang . 2019 . DARTS: Differentiable Architecture Search. In International Conference on Learning Representations. Hanxiao Liu, Karen Simonyan, and Yiming Yang. 2019. DARTS: Differentiable Architecture Search. In International Conference on Learning Representations."},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3449989"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3449896"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/3447548.3467312"},{"volume-title":"Lasagne: A multi-layer graph convolutional network framework via node-aware deep architecture","year":"2021","author":"Miao Xupeng","key":"e_1_3_2_1_33_1","unstructured":"Xupeng Miao , Wentao Zhang , Yingxia Shao , Bin Cui , Lei Chen , Ce Zhang , and Jiawei Jiang . 2021 . Lasagne: A multi-layer graph convolutional network framework via node-aware deep architecture . IEEE Transactions on Knowledge and Data Engineering ( 2021). Xupeng Miao, Wentao Zhang, Yingxia Shao, Bin Cui, Lei Chen, Ce Zhang, and Jiawei Jiang. 2021. Lasagne: A multi-layer graph convolutional network framework via node-aware deep architecture. IEEE Transactions on Knowledge and Data Engineering (2021)."},{"volume-title":"Geometric matrix completion with recurrent multi-graph neural networks. Advances in neural information processing systems 30","year":"2017","author":"Monti Federico","key":"e_1_3_2_1_34_1","unstructured":"Federico Monti , Michael Bronstein , and Xavier Bresson . 2017. Geometric matrix completion with recurrent multi-graph neural networks. Advances in neural information processing systems 30 ( 2017 ). Federico Monti, Michael Bronstein, and Xavier Bresson. 2017. Geometric matrix completion with recurrent multi-graph neural networks. Advances in neural information processing systems 30 (2017)."},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1109\/DSW.2018.8439897"},{"volume-title":"Geom-GCN: Geometric Graph Convolutional Networks. In International Conference on Learning Representations.","year":"2020","author":"Pei Hongbin","key":"e_1_3_2_1_36_1","unstructured":"Hongbin Pei , Bingzhe Wei , Kevin Chen-Chuan Chang , Yu Lei , and Bo Yang . 2020 . Geom-GCN: Geometric Graph Convolutional Networks. In International Conference on Learning Representations. Hongbin Pei, Bingzhe Wei, Kevin Chen-Chuan Chang, Yu Lei, and Bo Yang. 2020. Geom-GCN: Geometric Graph Convolutional Networks. In International Conference on Learning Representations."},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3449849"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3220077"},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3449882"},{"key":"e_1_3_2_1_40_1","unstructured":"Oleksandr Shchur Maximilian Mumme Aleksandar Bojchevski and Stephan G\u00fcnnemann. 2018. Pitfalls of graph neural network evaluation. arXiv preprint arXiv:1811.05868(2018). Oleksandr Shchur Maximilian Mumme Aleksandar Bojchevski and Stephan G\u00fcnnemann. 2018. Pitfalls of graph neural network evaluation. arXiv preprint arXiv:1811.05868(2018)."},{"key":"e_1_3_2_1_41_1","unstructured":"Yu Shen Yang Li Jian Zheng Wentao Zhang Peng Yao Jixiang Li Sen Yang Ji Liu and Cui Bin. 2021. ProxyBO: Accelerating Neural Architecture Search via Bayesian Optimization with Zero-cost Proxies. arXiv preprint arXiv:2110.10423(2021). Yu Shen Yang Li Jian Zheng Wentao Zhang Peng Yao Jixiang Li Sen Yang Ji Liu and Cui Bin. 2021. ProxyBO: Accelerating Neural Architecture Search via Bayesian Optimization with Zero-cost Proxies. arXiv preprint arXiv:2110.10423(2021)."},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.3025110"},{"volume-title":"15th USENIX Symposium on Operating Systems Design and Implementation (OSDI 21)","year":"2021","author":"Thorpe John","key":"e_1_3_2_1_43_1","unstructured":"John Thorpe , Yifan Qiao , Jonathan Eyolfson , Shen Teng , Guanzhou Hu , Zhihao Jia , Jinliang Wei , Keval Vora , Ravi Netravali , Miryung Kim , 2021 . Dorylus: Affordable, Scalable, and Accurate {GNN} Training with Distributed {CPU} Servers and Serverless Threads . In 15th USENIX Symposium on Operating Systems Design and Implementation (OSDI 21) . 495\u2013514. John Thorpe, Yifan Qiao, Jonathan Eyolfson, Shen Teng, Guanzhou Hu, Zhihao Jia, Jinliang Wei, Keval Vora, Ravi Netravali, Miryung Kim, 2021. Dorylus: Affordable, Scalable, and Accurate {GNN} Training with Distributed {CPU} Servers and Serverless Threads. In 15th USENIX Symposium on Operating Systems Design and Implementation (OSDI 21). 495\u2013514."},{"volume-title":"Graph Attention Networks. In International Conference on Learning Representations.","year":"2018","author":"Veli\u010dkovi\u0107 Petar","key":"e_1_3_2_1_44_1","unstructured":"Petar Veli\u010dkovi\u0107 , Guillem Cucurull , Arantxa Casanova , Adriana Romero , Pietro Li\u00f2 , and Yoshua Bengio . 2018 . Graph Attention Networks. In International Conference on Learning Representations. Petar Veli\u010dkovi\u0107, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Li\u00f2, and Yoshua Bengio. 2018. Graph Attention Networks. In International Conference on Learning Representations."},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2007.190672"},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1145\/3447786.3456229"},{"key":"e_1_3_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3449952"},{"key":"e_1_3_2_1_48_1","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3450118"},{"key":"e_1_3_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00717"},{"volume-title":"GNNAdvisor: An Adaptive and Efficient Runtime System for GNN Acceleration on GPUs. In 15th USENIX Symposium on Operating Systems Design and Implementation (OSDI 21)","year":"2021","author":"Wang Yuke","key":"e_1_3_2_1_50_1","unstructured":"Yuke Wang , Boyuan Feng , Gushu Li , Shuangchen Li , Lei Deng , Yuan Xie , and Yufei Ding . 2021 . GNNAdvisor: An Adaptive and Efficient Runtime System for GNN Acceleration on GPUs. In 15th USENIX Symposium on Operating Systems Design and Implementation (OSDI 21) . 515\u2013531. Yuke Wang, Boyuan Feng, Gushu Li, Shuangchen Li, Lei Deng, Yuan Xie, and Yufei Ding. 2021. GNNAdvisor: An Adaptive and Efficient Runtime System for GNN Acceleration on GPUs. In 15th USENIX Symposium on Operating Systems Design and Implementation (OSDI 21). 515\u2013531."},{"key":"e_1_3_2_1_51_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/142"},{"volume-title":"International conference on machine learning. PMLR, 6861\u20136871","year":"2019","author":"Wu Felix","key":"e_1_3_2_1_52_1","unstructured":"Felix Wu , Amauri Souza , Tianyi Zhang , Christopher Fifty , Tao Yu , and Kilian Weinberger . 2019 . Simplifying graph convolutional networks . In International conference on machine learning. PMLR, 6861\u20136871 . Felix Wu, Amauri Souza, Tianyi Zhang, Christopher Fifty, Tao Yu, and Kilian Weinberger. 2019. Simplifying graph convolutional networks. In International conference on machine learning. PMLR, 6861\u20136871."},{"key":"e_1_3_2_1_53_1","unstructured":"Shiwen Wu Fei Sun Wentao Zhang and Bin Cui. 2020. Graph neural networks in recommender systems: a survey. arXiv preprint arXiv:2011.02260(2020). Shiwen Wu Fei Sun Wentao Zhang and Bin Cui. 2020. Graph neural networks in recommender systems: a survey. arXiv preprint arXiv:2011.02260(2020)."},{"key":"e_1_3_2_1_54_1","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3449884"},{"key":"e_1_3_2_1_55_1","doi-asserted-by":"publisher","DOI":"10.1145\/3447786.3456247"},{"key":"e_1_3_2_1_56_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.2978386"},{"volume-title":"International Conference on Machine Learning. PMLR, 5453\u20135462","year":"2018","author":"Xu Keyulu","key":"e_1_3_2_1_57_1","unstructured":"Keyulu Xu , Chengtao Li , Yonglong Tian , Tomohiro Sonobe , Ken-ichi Kawarabayashi, and Stefanie Jegelka . 2018 . Representation learning on graphs with jumping knowledge networks . In International Conference on Machine Learning. PMLR, 5453\u20135462 . Keyulu Xu, Chengtao Li, Yonglong Tian, Tomohiro Sonobe, Ken-ichi Kawarabayashi, and Stefanie Jegelka. 2018. Representation learning on graphs with jumping knowledge networks. In International Conference on Machine Learning. PMLR, 5453\u20135462."},{"key":"e_1_3_2_1_58_1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219890"},{"key":"e_1_3_2_1_59_1","first-page":"17009","article-title":"Design space for graph neural networks","volume":"33","author":"You Jiaxuan","year":"2020","unstructured":"Jiaxuan You , Zhitao Ying , and Jure Leskovec . 2020 . Design space for graph neural networks . Advances in Neural Information Processing Systems 33 (2020), 17009 \u2013 17021 . Jiaxuan You, Zhitao Ying, and Jure Leskovec. 2020. Design space for graph neural networks. Advances in Neural Information Processing Systems 33 (2020), 17009\u201317021.","journal-title":"Advances in Neural Information Processing Systems"},{"volume-title":"GraphSAINT: Graph Sampling Based Inductive Learning Method. In International Conference on Learning Representations.","year":"2020","author":"Zeng Hanqing","key":"e_1_3_2_1_60_1","unstructured":"Hanqing Zeng , Hongkuan Zhou , Ajitesh Srivastava , Rajgopal Kannan , and Viktor Prasanna . 2020 . GraphSAINT: Graph Sampling Based Inductive Learning Method. In International Conference on Learning Representations. Hanqing Zeng, Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, and Viktor Prasanna. 2020. GraphSAINT: Graph Sampling Based Inductive Learning Method. In International Conference on Learning Representations."},{"key":"e_1_3_2_1_61_1","doi-asserted-by":"publisher","DOI":"10.1145\/3447548.3467221"},{"key":"e_1_3_2_1_62_1","unstructured":"Wentao Zhang Zeang Sheng Yuezihan Jiang Yikuan Xia Jun Gao Zhi Yang and Bin Cui. 2021. Evaluating deep graph neural networks. arXiv preprint arXiv:2108.00955(2021). Wentao Zhang Zeang Sheng Yuezihan Jiang Yikuan Xia Jun Gao Zhi Yang and Bin Cui. 2021. Evaluating deep graph neural networks. arXiv preprint arXiv:2108.00955(2021)."},{"volume-title":"Node Dependent Local Smoothing for Scalable Graph Learning. Advances in Neural Information Processing Systems 34","year":"2021","author":"Zhang Wentao","key":"e_1_3_2_1_63_1","unstructured":"Wentao Zhang , Mingyu Yang , Zeang Sheng , Yang Li , Wen Ouyang , Yangyu Tao , Zhi Yang , and Bin Cui . 2021. Node Dependent Local Smoothing for Scalable Graph Learning. Advances in Neural Information Processing Systems 34 ( 2021 ). Wentao Zhang, Mingyu Yang, Zeang Sheng, Yang Li, Wen Ouyang, Yangyu Tao, Zhi Yang, and Bin Cui. 2021. Node Dependent Local Smoothing for Scalable Graph Learning. Advances in Neural Information Processing Systems 34 (2021)."},{"key":"e_1_3_2_1_64_1","unstructured":"Wentao Zhang Ziqi Yin Zeang Sheng Wen Ouyang Xiaosen Li Yangyu Tao Zhi Yang and Bin Cui. 2021. Graph attention multi-layer perceptron. arXiv preprint arXiv:2108.10097(2021). Wentao Zhang Ziqi Yin Zeang Sheng Wen Ouyang Xiaosen Li Yangyu Tao Zhi Yang and Bin Cui. 2021. Graph attention multi-layer perceptron. arXiv preprint arXiv:2108.10097(2021)."},{"key":"e_1_3_2_1_65_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2021\/637"},{"key":"e_1_3_2_1_66_1","doi-asserted-by":"publisher","DOI":"10.1109\/IA351965.2020.00011"},{"volume-title":"Auto-gnn: Neural architecture search of graph neural networks. arXiv preprint arXiv:1909.03184(2019).","year":"2019","author":"Zhou Kaixiong","key":"e_1_3_2_1_67_1","unstructured":"Kaixiong Zhou , Qingquan Song , Xiao Huang , and Xia Hu . 2019 . Auto-gnn: Neural architecture search of graph neural networks. arXiv preprint arXiv:1909.03184(2019). Kaixiong Zhou, Qingquan Song, Xiao Huang, and Xia Hu. 2019. Auto-gnn: Neural architecture search of graph neural networks. arXiv preprint arXiv:1909.03184(2019)."},{"volume-title":"International Conference on Learning Representations.","year":"2021","author":"Zhu Hao","key":"e_1_3_2_1_68_1","unstructured":"Hao Zhu and Piotr Koniusz . 2021 . Simple spectral graph convolution . In International Conference on Learning Representations. Hao Zhu and Piotr Koniusz. 2021. Simple spectral graph convolution. In International Conference on Learning Representations."}],"event":{"name":"WWW '22: The ACM Web Conference 2022","sponsor":["SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web"],"location":"Virtual Event, Lyon France","acronym":"WWW '22"},"container-title":["Proceedings of the ACM Web Conference 2022"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3485447.3511986","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,4,25]],"date-time":"2023-04-25T09:08:32Z","timestamp":1682413712000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3485447.3511986"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,4,25]]},"references-count":68,"alternative-id":["10.1145\/3485447.3511986","10.1145\/3485447"],"URL":"http:\/\/dx.doi.org\/10.1145\/3485447.3511986","relation":{},"subject":[],"published":{"date-parts":[[2022,4,25]]},"assertion":[{"value":"2022-04-25","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}