{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T16:22:16Z","timestamp":1774023736886,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":15,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,5,13]],"date-time":"2024-05-13T00:00:00Z","timestamp":1715558400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,5,13]]},"DOI":"10.1145\/3589335.3651575","type":"proceedings-article","created":{"date-parts":[[2024,5,12]],"date-time":"2024-05-12T18:41:21Z","timestamp":1715539281000},"page":"903-906","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Turning A Curse into A Blessing: Data-Aware Memory-Efficient Training of Graph Neural Networks by Dynamic Exiting"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7164-2295","authenticated-orcid":false,"given":"Yan","family":"Han","sequence":"first","affiliation":[{"name":"LinkedIn, Sunnyvale, CA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-6279-0849","authenticated-orcid":false,"given":"Kaiqi","family":"Chen","sequence":"additional","affiliation":[{"name":"Amazon, Palo Alto, CA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-2822-2392","authenticated-orcid":false,"given":"Shan","family":"Li","sequence":"additional","affiliation":[{"name":"Nextdoor, Sunnyvale, CA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-7699-1430","authenticated-orcid":false,"given":"Ji","family":"Yan","sequence":"additional","affiliation":[{"name":"LinkedIn, Sunnyvale, CA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7026-5811","authenticated-orcid":false,"given":"Baoxu","family":"Shi","sequence":"additional","affiliation":[{"name":"Nextdoor, Sunnyvale, CA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-5506-9501","authenticated-orcid":false,"given":"Lei","family":"Zhang","sequence":"additional","affiliation":[{"name":"Meta, Mountain View, CA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-1378-7643","authenticated-orcid":false,"given":"Fei","family":"Chen","sequence":"additional","affiliation":[{"name":"Amazon, Palo Alto, CA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-2224-7915","authenticated-orcid":false,"given":"Jaewon","family":"Yang","sequence":"additional","affiliation":[{"name":"Nextdoor, Sunnyvale, CA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-5298-7327","authenticated-orcid":false,"given":"Yunpeng","family":"Xu","sequence":"additional","affiliation":[{"name":"LinkedIn, New York City, NY, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-9474-2977","authenticated-orcid":false,"given":"Xiaoqiang","family":"Luo","sequence":"additional","affiliation":[{"name":"LinkedIn, New York City, NY, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5257-6843","authenticated-orcid":false,"given":"Qi","family":"He","sequence":"additional","affiliation":[{"name":"Nextdoor, Sunnyvale, CA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2567-2009","authenticated-orcid":false,"given":"Ying","family":"Ding","sequence":"additional","affiliation":[{"name":"University of Texas at Austin, Austin, TX, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2050-5693","authenticated-orcid":false,"given":"Zhangyang","family":"Wang","sequence":"additional","affiliation":[{"name":"University of Texas at Austin, Austin, TX, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2024,5,13]]},"reference":[{"key":"e_1_3_2_2_1_1","volume-title":"Fastgcn: fast learning with graph convolutional networks via importance sampling. arXiv preprint arXiv:1801.10247","author":"Chen Jie","year":"2018","unstructured":"Jie Chen, Tengfei Ma, and Cao Xiao. 2018. Fastgcn: fast learning with graph convolutional networks via importance sampling. arXiv preprint arXiv:1801.10247 (2018)."},{"key":"e_1_3_2_2_2_1","first-page":"6733","article-title":"VQ-GNN: A Universal Framework to Scale up Graph Neural Networks using Vector Quantization","volume":"34","author":"Ding Mucong","year":"2021","unstructured":"Mucong Ding, Kezhi Kong, Jingling Li, Chen Zhu, John Dickerson, Furong Huang, and Tom Goldstein. 2021. VQ-GNN: A Universal Framework to Scale up Graph Neural Networks using Vector Quantization. Advances in Neural Information Processing Systems , Vol. 34 (2021), 6733--6746.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_2_3_1","volume-title":"International Conference on Machine Learning. PMLR, 3294--3304","author":"Fey Matthias","year":"2021","unstructured":"Matthias Fey, Jan E Lenssen, Frank Weichert, and Jure Leskovec. 2021. Gnnautoscale: Scalable and expressive graph neural networks via historical embeddings. In International Conference on Machine Learning. PMLR, 3294--3304."},{"key":"e_1_3_2_2_4_1","unstructured":"Alex M Fout. 2017. Protein interface prediction using graph convolutional networks. Ph.D. Dissertation. Colorado State University."},{"key":"e_1_3_2_2_5_1","unstructured":"Will Hamilton Zhitao Ying and Jure Leskovec. 2017. Inductive representation learning on large graphs. In NeuIPS. 1024--1034."},{"key":"e_1_3_2_2_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/3437963.3441738"},{"key":"e_1_3_2_2_7_1","volume-title":"Adaptive sampling towards fast graph representation learning. arXiv preprint arXiv:1809.05343","author":"Huang Wenbing","year":"2018","unstructured":"Wenbing Huang, Tong Zhang, Yu Rong, and Junzhou Huang. 2018. Adaptive sampling towards fast graph representation learning. arXiv preprint arXiv:1809.05343 (2018)."},{"key":"e_1_3_2_2_8_1","volume-title":"Semi-supervised classification with graph convolutional networks. ICLR","author":"Kipf Thomas N","year":"2017","unstructured":"Thomas N Kipf and Max Welling. 2017. Semi-supervised classification with graph convolutional networks. ICLR (2017)."},{"key":"e_1_3_2_2_9_1","volume-title":"Fastbert: a self-distilling bert with adaptive inference time. arXiv preprint arXiv:2004.02178","author":"Liu Weijie","year":"2020","unstructured":"Weijie Liu, Peng Zhou, Zhe Zhao, Zhiruo Wang, Haotang Deng, and Qi Ju. 2020. Fastbert: a self-distilling bert with adaptive inference time. arXiv preprint arXiv:2004.02178 (2020)."},{"key":"e_1_3_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00144"},{"key":"e_1_3_2_2_11_1","volume-title":"Ivan Titov, and Max Welling.","author":"Schlichtkrull Michael","year":"2018","unstructured":"Michael Schlichtkrull, Thomas N Kipf, Peter Bloem, Rianne Van Den Berg, Ivan Titov, and Max Welling. 2018. Modeling relational data with graph convolutional networks. In European semantic web conference. Springer, 593--607."},{"key":"e_1_3_2_2_12_1","volume-title":"Degree-quant: Quantization-aware training for graph neural networks. arXiv preprint arXiv:2008.05000","author":"Tailor Shyam A","year":"2020","unstructured":"Shyam A Tailor, Javier Fernandez-Marques, and Nicholas D Lane. 2020. Degree-quant: Quantization-aware training for graph neural networks. arXiv preprint arXiv:2008.05000 (2020)."},{"key":"e_1_3_2_2_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3450068"},{"key":"e_1_3_2_2_14_1","volume-title":"Graphsaint: Graph sampling based inductive learning method. arXiv preprint arXiv:1907.04931","author":"Zeng Hanqing","year":"2019","unstructured":"Hanqing Zeng, Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, and Viktor Prasanna. 2019. Graphsaint: Graph sampling based inductive learning method. arXiv preprint arXiv:1907.04931 (2019)."},{"key":"e_1_3_2_2_15_1","volume-title":"Accelerating large scale real-time GNN inference using channel pruning. arXiv preprint arXiv:2105.04528","author":"Zhou Hongkuan","year":"2021","unstructured":"Hongkuan Zhou, Ajitesh Srivastava, Hanqing Zeng, Rajgopal Kannan, and Viktor Prasanna. 2021. Accelerating large scale real-time GNN inference using channel pruning. arXiv preprint arXiv:2105.04528 (2021). io"}],"event":{"name":"WWW '24: The ACM Web Conference 2024","location":"Singapore Singapore","acronym":"WWW '24","sponsor":["SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web"]},"container-title":["Companion Proceedings of the ACM Web Conference 2024"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3589335.3651575","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3589335.3651575","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T00:32:46Z","timestamp":1755822766000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3589335.3651575"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,5,13]]},"references-count":15,"alternative-id":["10.1145\/3589335.3651575","10.1145\/3589335"],"URL":"https:\/\/doi.org\/10.1145\/3589335.3651575","relation":{},"subject":[],"published":{"date-parts":[[2024,5,13]]},"assertion":[{"value":"2024-05-13","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}